private void SetUpFisII()
{
//Input
var impact = new LinguisticVariable("Impact", 0, 100);
new List <FuzzySet>()
{
new FuzzySet("Low", new TrapezoidalFunction(0, 5, 25, 30)),
new FuzzySet("Medium", new TrapezoidalFunction(20, 25, 55, 60)),
new FuzzySet("High", new TrapezoidalFunction(50, 55, 95, 100))
}.ForEach(x => impact.AddLabel(x));
var onGround = new LinguisticVariable("On_ground", -0.5f, 1.5f);
new List <FuzzySet>()
{
new FuzzySet("Low", new TrapezoidalFunction(-0.5f, -0.2f, 0.2f, 0.5f)),
new FuzzySet("Medium", new TrapezoidalFunction(0.1f, 0.5f, 0.5f, 0.9f)),
new FuzzySet("High", new TrapezoidalFunction(0.5f, 0.8f, 1.2f, 1.5f))
}.ForEach(x => onGround.AddLabel(x));
var timeOnGround = new LinguisticVariable("Time_on_ground", -1, 901);
new List <FuzzySet>()
{
new FuzzySet("Brief", new TrapezoidalFunction(-1, 1, 1, 2)),
new FuzzySet("Short", new TrapezoidalFunction(1, 5, 10, 15)),
new FuzzySet("Moderate", new TrapezoidalFunction(10, 120, 480, 720)),
new FuzzySet("Long", new TrapezoidalFunction(480, 900, 900, 901))
}.ForEach(x => timeOnGround.AddLabel(x));
//Output
var fallWearable = new LinguisticVariable("Fall_wearable", -0.5f, 1.5f);
new List <FuzzySet>()
{
new FuzzySet("Low", new TrapezoidalFunction(-0.5f, -0.2f, 0.2f, 0.5f)),
new FuzzySet("Medium", new TrapezoidalFunction(0.1f, 0.5f, 0.5f, 0.9f)),
new FuzzySet("High", new TrapezoidalFunction(0.5f, 0.8f, 1.2f, 1.5f))
}.ForEach(x => fallWearable.AddLabel(x));
var db = new Database();
db.AddVariable(impact);
db.AddVariable(onGround);
db.AddVariable(timeOnGround);
db.AddVariable(fallWearable);
fisII = new InferenceSystem(db, new CentroidDefuzzifier(1000));
fisII.NewRule("Rule 1", "IF Impact IS High AND On_ground IS High AND Time_on_ground IS Long THEN Fall_wearable IS High");
fisII.NewRule("Rule 2", "IF Impact IS Medium AND On_ground IS High AND Time_on_ground IS Long THEN Fall_wearable IS High");
fisII.NewRule("Rule 3", "IF Impact IS Low AND On_ground IS Low AND (Time_on_ground IS Short OR Time_on_ground IS Brief) THEN Fall_wearable IS Low");
fisII.NewRule("Rule 4", "IF Impact IS Medium AND On_ground IS Medium AND Time_on_ground IS Moderate THEN Fall_wearable IS Medium");
fisII.NewRule("Rule 5", "IF Impact IS High AND On_ground IS Medium AND (Time_on_ground IS Short OR Time_on_ground IS Brief) THEN Fall_wearable IS Medium");
}
private void Rules()
{
infSystem = new InferenceSystem(database, new CentroidDefuzzifier(120));
infSystem.NewRule("Rule 1", "IF Distance IS Far THEN Speed IS Slow"); //AITank Player tanka uzaksa yavaş
infSystem.NewRule("Rule 2", "IF Distance IS Medi THEN Speed IS Medium"); // AITank Player tanka orta uzaklıkta ise orta hızda
infSystem.NewRule("Rule 3", "IF Distance IS Near THEN Speed IS Fast"); //AITank Player tanka yakınsa hızlı gidecek
}
private void SetUpFisI()
{
//Input
var treshhold = new LinguisticVariable("Threshold", 0, 100);
new List <FuzzySet>()
{
new FuzzySet("Low", new TrapezoidalFunction(0, 5, 25, 30)),
new FuzzySet("Medium", new TrapezoidalFunction(20, 25, 55, 60)),
new FuzzySet("High", new TrapezoidalFunction(50, 55, 95, 100))
}.ForEach(x => treshhold.AddLabel(x));
//Output
var impact = new LinguisticVariable("Impact", 0, 100);
new List <FuzzySet>()
{
new FuzzySet("Low", new TrapezoidalFunction(0, 5, 25, 30)),
new FuzzySet("Medium", new TrapezoidalFunction(20, 25, 55, 60)),
new FuzzySet("High", new TrapezoidalFunction(50, 55, 95, 100))
}.ForEach(x => impact.AddLabel(x));
var db = new Database();
db.AddVariable(treshhold);
db.AddVariable(impact);
fisI = new InferenceSystem(db, new CentroidDefuzzifier(1000));
fisI.NewRule("Rule 1", "IF Threshold IS Low THEN Impact IS Low");
fisI.NewRule("Rule 2", "IF Threshold IS Medium THEN Impact IS Medium");
fisI.NewRule("Rule 3", "IF Threshold IS High THEN Impact IS High");
}
private void SetRules()
{
infSystem = new InferenceSystem(database, new CentroidDefuzzifier(120));
infSystem.NewRule("Rule 1", "IF Distance IS Near THEN Speed IS Slow");
infSystem.NewRule("Rule 2", "IF Distance IS Med THEN Speed IS Medium");
infSystem.NewRule("Rule 3", "IF Distance IS Far THEN Speed IS Fast");
}
public InferenceSystem SetupInferenceSystem(int width)
{
var mp = new TrapezoidalFunction(centerPoint - width / 2, centerPoint, centerPoint + width / 2);
var mn = new TrapezoidalFunction(-centerPoint - width / 2, -centerPoint, -centerPoint + width / 2);
var sp = new TrapezoidalFunction(-centerPoint / 2 + width / 4, (double)centerPoint / 2, centerPoint / 2 + width / 3);
var sn = new TrapezoidalFunction(-centerPoint / 2 - width / 3, (double)-centerPoint / 2, centerPoint / 2 - width / 4);
var ze = new TrapezoidalFunction(-(double)centerPoint / 4, 0, (double)centerPoint / 4);
var mpSet = new FuzzySet("MP", mp);
var mnSet = new FuzzySet("MN", mn);
var spSet = new FuzzySet("SP", sp);
var snSet = new FuzzySet("SN", sn);
var zeSet = new FuzzySet("ZE", ze);
var ruleDatabase = new Database();
for (int i = 0; i < windowSize * windowSize - 1; i++)
{
var variable = new LinguisticVariable(String.Format("IN{0}", i), -255, 255);
variable.AddLabel(mpSet);
variable.AddLabel(mnSet);
ruleDatabase.AddVariable(variable);
}
var outVariable = new LinguisticVariable("OUT", -centerPoint - width / 2, centerPoint + width / 2);
outVariable.AddLabel(spSet);
outVariable.AddLabel(snSet);
outVariable.AddLabel(zeSet);
ruleDatabase.AddVariable(outVariable);
var inferenceSystem = new InferenceSystem(ruleDatabase, new CentroidDefuzzifier(100));
string rule1 = "IF ";
string rule2 = "IF ";
string rule3 = "IF ";
for (int i = 0; i < windowSize * windowSize - 1; i++)
{
rule1 += String.Format("IN{0} is MP and ", i);
rule2 += String.Format("IN{0} is MN and ", i);
rule3 += String.Format("IN{0} is not MP and IN{0} is not MN AND ", i);
}
rule1 = rule1.Remove(rule1.Length - 4, 4);
rule2 = rule2.Remove(rule2.Length - 4, 4);
rule3 = "IF NOT (" + rule1.Replace("IF", "") + ") AND NOT(" + rule2.Replace("IF", "") + ")";
rule1 += " then OUT is SN";
rule2 += " then OUT is SP";
rule3 += " then OUT is ZE";
inferenceSystem.NewRule("Rule1", rule1);
inferenceSystem.NewRule("Rule2", rule2);
inferenceSystem.NewRule("Rule3", rule3);
return(inferenceSystem);
}
public ZoomGps()
{
// création du langage
var ld = LinguistictDistance();
var lv = LinguisticVitesse();
var lz = LinguisticZoom();
// création des règles
Database fuzzyDB = new Database();
fuzzyDB.AddVariable(ld);
fuzzyDB.AddVariable(lv);
fuzzyDB.AddVariable(lz);
var IS = new InferenceSystem(fuzzyDB, new CentroidDefuzzifier(100));
IS.NewRule("Rule 1", "IF Distance IS Grande THEN Zoom IS Petit");
IS.NewRule("Rule 2", "IF Distance IS Faible AND Vitesse IS Lente THEN Zoom IS Normal");
IS.NewRule("Rule 3", "IF Distance IS Faible AND Vitesse IS PeuRapide THEN Zoom IS Normal");
IS.NewRule("Rule 4", "IF Distance IS Faible AND Vitesse IS Rapide THEN Zoom IS Gros");
IS.NewRule("Rule 5", "IF Distance IS Faible AND Vitesse IS TresRapide THEN Zoom IS Gros");
IS.NewRule("Rule 6", "IF Distance IS Moyenne AND Vitesse IS Lente THEN Zoom IS Petit");
IS.NewRule("Rule 7", "IF Distance IS Moyenne AND Vitesse IS PeuRapide THEN Zoom IS Normal");
IS.NewRule("Rule 8", "IF Distance IS Moyenne AND Vitesse IS Rapide THEN Zoom IS Normal");
IS.NewRule("Rule 9", "IF Distance IS Moyenne AND Vitesse IS TresRapide THEN Zoom IS Gros");
m_IS = IS;
}
private void AddToDatabese()
{
database = new Database();
database.AddVariable(lvDistance);
database.AddVariable(lvSpeed);
infSystem = new InferenceSystem(database, new CentroidDefuzzifier(20));
infSystem.NewRule("Rule1", "IF Distance IS Near THEN Speed IS Slow");
infSystem.NewRule("Rule2", "IF Distance IS Med THEN Speed IS Medium");
infSystem.NewRule("Rule3", "IF Distance IS Far THEN Speed IS Fast");
}
private void Initialize(List <Variable> variables, List <String> roles)
{
_fuzzyDB = new Database();
foreach (var variable in variables)
{
_fuzzyDB.AddVariable(variable.FVariable);
if (variable.Type == JConfig.VariableType.Ouput)
{
_outputName = variable.FVariable.Name;
}
}
_centroidDefuzzifier = new CentroidDefuzzifier(1000);
_system = new InferenceSystem(_fuzzyDB, _centroidDefuzzifier);
foreach (var variable in variables)
{
if (variable.Type == JConfig.VariableType.Input)
{
_system.SetInput(variable.Name, (float)variable.ResultValue);
}
}
int roleCounter = 0;
foreach (var role in roles)
{
_system.NewRule("Role " + roleCounter++, role);
}
}
private InferenceSystem SetupInferenceSystem(byte minLuma, byte maxLuma, byte meanLuma)
{
var lumaIn = new LinguisticVariable("LumaIn", minLuma, maxLuma);
var lumaOut = new LinguisticVariable("LumaOut", 0, 255);
var darkFunction = new TrapezoidalFunction(minLuma, meanLuma, TrapezoidalFunction.EdgeType.Right);
var darkSet = new FuzzySet("Dark", darkFunction);
var mediumFunction = new TrapezoidalFunction(minLuma, meanLuma, maxLuma);
var mediumSet = new FuzzySet("Medium", mediumFunction);
var lightFunction = new TrapezoidalFunction(meanLuma, maxLuma, TrapezoidalFunction.EdgeType.Left);
var lightSet = new FuzzySet("Light", lightFunction);
lumaIn.AddLabel(darkSet);
lumaIn.AddLabel(mediumSet);
lumaIn.AddLabel(lightSet);
var whiteFunction = new SingletonFunction(255);
var whiteSet = new FuzzySet("White", whiteFunction);
var blackFunction = new SingletonFunction(0);
var blackSet = new FuzzySet("Black", blackFunction);
var grayFunction = new SingletonFunction(128);
var graySet = new FuzzySet("Gray", grayFunction);
lumaOut.AddLabel(blackSet);
lumaOut.AddLabel(graySet);
lumaOut.AddLabel(whiteSet);
var database = new Database();
database.AddVariable(lumaIn);
database.AddVariable(lumaOut);
var inferenceSystem = new InferenceSystem(database, new CogDefuzzifier());
inferenceSystem.NewRule("Rule 1", "IF LumaIn IS Dark THEN LumaOut is Black");
inferenceSystem.NewRule("Rule 2", "IF LumaIn IS Medium THEN LumaOut is Gray");
inferenceSystem.NewRule("Rule 3", "IF LumaIn IS Light THEN LumaOut is White");
return(inferenceSystem);
}
private void InitFuzz()
{
this.Charts = new List <FuzzySetGroupCharts>();
Database db = new Database();
// fuzzy set to determine perceived distance
FuzzySetGroupDesc distanceGroup = new FuzzySetGroupDesc("Distance");
distanceGroup.Add(new FuzzySetDescLeft("Near", 0.75f, 2.5f));
distanceGroup.Add(new FuzzySetDescMid("Medium", 0.75f, 2.5f, 3, 10));
distanceGroup.Add(new FuzzySetDescRight("Far", 3, 10));
this.Charts.Add(new FuzzySetGroupCharts(distanceGroup));
FuzzySet[] distanceSets = FuzzUtil.CreateFuzzySets(distanceGroup);
db.AddVariable(FuzzUtil.CreateVariable("RightDistance", 0, 10, distanceSets));
db.AddVariable(FuzzUtil.CreateVariable("LeftDistance", 0, 10, distanceSets));
db.AddVariable(FuzzUtil.CreateVariable("FrontDistance", 0, 10, distanceSets));
// fuzzy set to determine heading directions
FuzzySetGroupDesc headingGroup = new FuzzySetGroupDesc("Heading");
headingGroup.Add(new FuzzySetDescLeft("HardLeft", -35, -30));
headingGroup.Add(new FuzzySetDescMid("Left", -35, -30, -20, -15));
headingGroup.Add(new FuzzySetDescMid("SlightLeft", -20, -15, -5, 0));
headingGroup.Add(new FuzzySetDescMid("Straight", -5, -1, 1, 5));
headingGroup.Add(new FuzzySetDescMid("SlightRight", 0, 5, 15, 20));
headingGroup.Add(new FuzzySetDescMid("Right", 15, 20, 30, 35));
headingGroup.Add(new FuzzySetDescRight("HardRight", 30, 35));
this.Charts.Add(new FuzzySetGroupCharts(headingGroup));
FuzzySet[] headingSets = FuzzUtil.CreateFuzzySets(headingGroup);
db.AddVariable(FuzzUtil.CreateVariable("Heading", -50, 50, headingSets));
_inferenceSystem = new InferenceSystem(db, new CentroidDefuzzifier(50));
// if all is clear ahead go for it
_inferenceSystem.NewRule("1", "IF FrontDistance IS Far THEN Heading IS Straight");
// should handle left/right turns
_inferenceSystem.NewRule("2", "IF FrontDistance IS Near AND RightDistance IS Near THEN Heading IS Left");
_inferenceSystem.NewRule("3", "IF FrontDistance IS Near AND LeftDistance IS Near THEN Heading IS Right");
// edge away from walls
_inferenceSystem.NewRule("4", "IF LeftDistance IS Near AND (RightDistance IS Medium OR RightDistance IS Far) THEN Heading IS SlightRight");
_inferenceSystem.NewRule("5", "IF RightDistance IS Near AND (LeftDistance IS Medium OR LeftDistance IS Far) THEN Heading IS SlightLeft");
// attempt to give priority to left turns if both are available?
_inferenceSystem.NewRule("6", "IF FrontDistance IS Near THEN Heading IS Left");
}
public FuzzyContainer()
{
registredVariables = new List <string>();
//var HR = new LinguisticVariable("HR", 0, 200);
//new List<FuzzySet>()
//{
// new FuzzySet("Low", new TrapezoidalFunction(0, 5, 45, 50)),
// new FuzzySet("Medium", new TrapezoidalFunction(50, 55, 115, 120)),
// new FuzzySet("High", new TrapezoidalFunction(120, 125, 195 ,200))
//}.ForEach(x => HR.AddLabel(x));
var impact = new LinguisticVariable("IMPACT", 0, 100);
new List <FuzzySet>()
{
new FuzzySet("Low", new TrapezoidalFunction(0, 5, 25, 30)),
new FuzzySet("Medium", new TrapezoidalFunction(20, 25, 55, 60)),
new FuzzySet("High", new TrapezoidalFunction(50, 55, 95, 100))
}.ForEach(x => impact.AddLabel(x));
registredVariables.Add(impact.Name);
Console.WriteLine("IMPACT name: " + impact.Name);
var onGround = new LinguisticVariable("ON_GROUND", -0.5f, 1.5f);
new List <FuzzySet>()
{
new FuzzySet("Low", new TrapezoidalFunction(-0.5f, -0.2f, 0.2f, 0.5f)),
new FuzzySet("Medium", new TrapezoidalFunction(0.1f, 0.5f, 0.5f, 0.9f)),
new FuzzySet("High", new TrapezoidalFunction(0.5f, 0.8f, 1.2f, 1.5f))
}.ForEach(x => onGround.AddLabel(x));
registredVariables.Add(onGround.Name);
var timeOnGround = new LinguisticVariable("TIME_ON_GROUND", -1, 901);
new List <FuzzySet>()
{
new FuzzySet("Brief", new TrapezoidalFunction(-1, 1, 1, 2)),
new FuzzySet("Short", new TrapezoidalFunction(1, 5, 10, 15)),
new FuzzySet("Moderate", new TrapezoidalFunction(10, 120, 480, 720)),
new FuzzySet("Long", new TrapezoidalFunction(480, 900, 900, 901))
}.ForEach(x => timeOnGround.AddLabel(x));
registredVariables.Add(timeOnGround.Name);
//Output
var fallWearable = new LinguisticVariable("FALL", -0.5f, 1.5f);
new List <FuzzySet>()
{
new FuzzySet("Low", new TrapezoidalFunction(-0.5f, -0.2f, 0.2f, 0.5f)),
new FuzzySet("Medium", new TrapezoidalFunction(0.1f, 0.5f, 0.5f, 0.9f)),
new FuzzySet("High", new TrapezoidalFunction(0.5f, 0.8f, 1.2f, 1.5f))
}.ForEach(x => fallWearable.AddLabel(x));
//var heartRate = new LinguisticVariable("HEART_RATE", 0, 100);
//new List<FuzzySet>()
//{
// new FuzzySet("Low", new TrapezoidalFunction(0, 5, 25, 30)),
// new FuzzySet("Medium", new TrapezoidalFunction(20, 25, 55, 60)),
// new FuzzySet("High", new TrapezoidalFunction(50, 55, 95 ,100))
//}.ForEach(x => heartRate.AddLabel(x));
var db = new Database();
//db.AddVariable(HR);
//db.AddVariable(heartRate);
db.AddVariable(impact);
db.AddVariable(onGround);
db.AddVariable(timeOnGround);
db.AddVariable(fallWearable);
fis = new InferenceSystem(db, new CentroidDefuzzifier(1000));
// fis.NewRule("Rule 1", "IF HR IS Low THEN HEART_RATE IS Low");
//fis.NewRule("Rule 2", "IF HR IS Medium THEN HEART_RATE IS Medium");
//fis.NewRule("Rule 3", "IF HR IS High THEN HEART_RATE IS High");
fis.NewRule("Rule 4", "IF IMPACT IS High AND ON_GROUND IS High AND TIME_ON_GROUND IS Long THEN FALL IS High");
fis.NewRule("Rule 5", "IF IMPACT IS Medium AND ON_GROUND IS High AND TIME_ON_GROUND IS Long THEN FALL IS High");
fis.NewRule("Rule 6", "IF IMPACT IS Low AND ON_GROUND IS Low AND (TIME_ON_GROUND IS Short OR TIME_ON_GROUND IS Brief) THEN FALL IS Low");
fis.NewRule("Rule 7", "IF IMPACT IS Medium AND ON_GROUND IS Medium AND TIME_ON_GROUND IS Moderate THEN FALL IS Medium");
fis.NewRule("Rule 8", "IF IMPACT IS High AND ON_GROUND IS Medium AND (TIME_ON_GROUND IS Short OR TIME_ON_GROUND IS Brief) THEN FALL IS Medium");
e2l = new EventToLabel();
}
//Definición del sistema de lógica difusa
void InitFuzzyEngine()
{
//Funciones de Pertenencia
//Demanda
FuzzySet fsBaja = new FuzzySet("Baja", new TrapezoidalFunction(2f, 4f, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsMedia = new FuzzySet("Media", new TrapezoidalFunction(3f, 5f, 7f));
FuzzySet fsAlta = new FuzzySet("Alta", new TrapezoidalFunction(6f, 8f, TrapezoidalFunction.EdgeType.Left));
//Disponible
FuzzySet fsPoco = new FuzzySet("Poco", new TrapezoidalFunction(4f, 8f, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsNormal = new FuzzySet("Normal", new TrapezoidalFunction(6f, 10f, 14f));
FuzzySet fsMucho = new FuzzySet("Mucho", new TrapezoidalFunction(12f, 16f, TrapezoidalFunction.EdgeType.Left));
//Fuerzas
FuzzySet fsPbaja = new FuzzySet("Pbaja", new TrapezoidalFunction(0.1f, 0.2f, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsPmedia = new FuzzySet("Pmedia", new TrapezoidalFunction(0.3f, 0.5f, 0.7f));
FuzzySet fsPalta = new FuzzySet("Palta", new TrapezoidalFunction(0.6f, 0.8f, TrapezoidalFunction.EdgeType.Left));
//Entradas
//Altura
LinguisticVariable lvDemanda = new LinguisticVariable("Demanda", 0, 10);
lvDemanda.AddLabel(fsBaja);
lvDemanda.AddLabel(fsMedia);
lvDemanda.AddLabel(fsAlta);
//Velocidades
LinguisticVariable lvDisponible = new LinguisticVariable("Disponible", 0, 20);
lvDisponible.AddLabel(fsPoco);
lvDisponible.AddLabel(fsNormal);
lvDisponible.AddLabel(fsMucho);
//Fuerzas
LinguisticVariable lvFuerza = new LinguisticVariable("Prioridad", 0, 1);
lvFuerza.AddLabel(fsPbaja);
lvFuerza.AddLabel(fsPmedia);
lvFuerza.AddLabel(fsPalta);
//La base de datos
Database fuzzyDb = new Database();
fuzzyDb.AddVariable(lvDemanda);
fuzzyDb.AddVariable(lvFuerza);
fuzzyDb.AddVariable(lvDisponible);
//Sistema de interferencia
ISL = new InferenceSystem(fuzzyDb, new CentroidDefuzzifier(800));
//Definicion de reglas
ISL.NewRule("Rule 1", "IF Demanda IS Baja AND Disponible IS Poco THEN Prioridad IS Pmedia");
ISL.NewRule("Rule 2", "IF Demanda IS Baja AND Disponible IS Normal THEN Prioridad IS Pbaja");
ISL.NewRule("Rule 3", "IF Demanda IS Baja AND Disponible IS Mucho THEN Prioridad IS Pbaja");
ISL.NewRule("Rule 4", "IF Demanda IS Media AND Disponible IS Poco THEN Prioridad IS Palta");
ISL.NewRule("Rule 5", "IF Demanda IS Media AND Disponible IS Normal THEN Prioridad IS Pbaja");
ISL.NewRule("Rule 6", "IF Demanda IS Media AND Disponible IS Mucho THEN Prioridad IS Pbaja");
ISL.NewRule("Rule 7", "IF Demanda IS Alta AND Disponible IS Poco THEN Prioridad IS Palta");
ISL.NewRule("Rule 8", "IF Demanda IS Alta AND Disponible IS Normal THEN Prioridad IS Pmedia");
ISL.NewRule("Rule 9", "IF Demanda IS Alta AND Disponible IS Mucho THEN Prioridad IS Pbaja");
}
private void Form1_Load(object sender, EventArgs e)
{
/*
* LinguisticVariable lvTemperature = new LinguisticVariable("Temperature", 0, 80);
*
* TrapezoidalFunction function1 = new TrapezoidalFunction(10, 15, TrapezoidalFunction.EdgeType.Right);
* FuzzySet fsCold = new FuzzySet("Cold", function1);
* TrapezoidalFunction function2 = new TrapezoidalFunction(10, 15, 20, 25);
* FuzzySet fsCool = new FuzzySet("Cool", function2);
* TrapezoidalFunction function3 = new TrapezoidalFunction(20, 25, 30, 35);
* FuzzySet fsWarm = new FuzzySet("Warm", function3);
* TrapezoidalFunction function4 = new TrapezoidalFunction(30, 35, TrapezoidalFunction.EdgeType.Left);
* FuzzySet fsHot = new FuzzySet("Hot", function4);
*
* lvTemperature.AddLabel(fsCold);
* lvTemperature.AddLabel(fsCool);
* lvTemperature.AddLabel(fsWarm);
* lvTemperature.AddLabel(fsHot);
*
* textBox1.Text += "Cold; Cool; Warm; Hot" + Environment.NewLine;
* for (float x = 0; x < 80; x += 0.2f)
* {
* float y1 = lvTemperature.GetLabelMembership("Cold", x);
* float y2 = lvTemperature.GetLabelMembership("Cool", x);
* float y3 = lvTemperature.GetLabelMembership("Warm", x);
* float y4 = lvTemperature.GetLabelMembership("Hot", x);
*
* textBox1.Text += y1.ToString() + " " + y2.ToString() + " " + y3.ToString() + " " + y4.ToString() + Environment.NewLine;
* }
*/
/*
* FuzzySet fsNear = new FuzzySet("Near", new TrapezoidalFunction(15, 50, TrapezoidalFunction.EdgeType.Right));
* FuzzySet fsMedium = new FuzzySet("Medium", new TrapezoidalFunction(15, 50, 60, 100));
* FuzzySet fsFar = new FuzzySet("Far", new TrapezoidalFunction(60, 100, TrapezoidalFunction.EdgeType.Left));
*
* LinguisticVariable lvFront = new LinguisticVariable("FrontalDistance", 0, 120);
* lvFront.AddLabel(fsNear);
* lvFront.AddLabel(fsMedium);
* lvFront.AddLabel(fsFar);
*
* FuzzySet fsZero = new FuzzySet("Zero", new TrapezoidalFunction(-10, 5, 5, 10));
* FuzzySet fsLP = new FuzzySet("LittlePositive", new TrapezoidalFunction(5, 10, 20, 25));
* FuzzySet fsP = new FuzzySet("Positive", new TrapezoidalFunction(20, 25, 35, 40));
* FuzzySet fsVP = new FuzzySet("VeryPositive", new TrapezoidalFunction(35, 40, TrapezoidalFunction.EdgeType.Left));
*
* LinguisticVariable lvAngle = new LinguisticVariable("Angle", -10, 50);
* lvAngle.AddLabel(fsZero);
* lvAngle.AddLabel(fsLP);
* lvAngle.AddLabel(fsP);
* lvAngle.AddLabel(fsVP);
*
* Database fuzzyDB = new Database();
* fuzzyDB.AddVariable(lvFront);
* fuzzyDB.AddVariable(lvAngle);
*
* InferenceSystem IS = new InferenceSystem(fuzzyDB, new CentroidDefuzzifier(1000));
*
* IS.NewRule("Rule 1", "IF FrontalDistance IS Far THEN Angle IS Zero");
* IS.NewRule("Rule 2", "IF FrontalDistance IS Near THEN Angle IS Positive");
*
* IS.SetInput("FrontalDistance", 20);
* float a = IS.Evaluate("Angle"); // -> 29.999
*
* try
* {
* FuzzyOutput fuzzyOutput = IS.ExecuteInference("Angle"); // -> 0.87 Positive
*
* foreach (FuzzyOutput.OutputConstraint oc in fuzzyOutput.OutputList)
* {
* Console.WriteLine(oc.Label + " - " + oc.FiringStrength.ToString());
* }
* }
* catch (Exception)
* {
* }*/
FuzzySet fsxM2 = new FuzzySet("xM2", new TrapezoidalFunction(-150, -80, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsxM1 = new FuzzySet("xM1", new TrapezoidalFunction(-90f, -65f, 0f));
FuzzySet fsxS = new FuzzySet("xS", new TrapezoidalFunction(-30f, 0, 30f));
FuzzySet fsxD1 = new FuzzySet("xD1", new TrapezoidalFunction(0f, 65f, 90f));
FuzzySet fsxD2 = new FuzzySet("xD2", new TrapezoidalFunction(80, 150, TrapezoidalFunction.EdgeType.Left));
LinguisticVariable lvX = new LinguisticVariable("XDist", -150, 150);
lvX.AddLabel(fsxM2);
lvX.AddLabel(fsxM1);
lvX.AddLabel(fsxS);
lvX.AddLabel(fsxD1);
lvX.AddLabel(fsxD2);
FuzzySet fsfM3 = new FuzzySet("fM3", new TrapezoidalFunction(-190, -140, -90));
FuzzySet fsfM2 = new FuzzySet("fM2", new TrapezoidalFunction(-140f, -90f, -45f));
FuzzySet fsfM1 = new FuzzySet("fM1", new TrapezoidalFunction(-90f, -45f, 0f));
FuzzySet fsfS = new FuzzySet("fS", new TrapezoidalFunction(-30f, 0, 30f));
FuzzySet fsfD1 = new FuzzySet("fD1", new TrapezoidalFunction(0f, 45f, 90f));
FuzzySet fsfD2 = new FuzzySet("fD2", new TrapezoidalFunction(45f, 90f, 140f));
FuzzySet fsfD3 = new FuzzySet("fD3", new TrapezoidalFunction(90, 140, 190));
LinguisticVariable lvF = new LinguisticVariable("FAngle", -190, 190);
lvF.AddLabel(fsfM3);
lvF.AddLabel(fsfM2);
lvF.AddLabel(fsfM1);
lvF.AddLabel(fsfS);
lvF.AddLabel(fsfD1);
lvF.AddLabel(fsfD2);
lvF.AddLabel(fsfD3);
FuzzySet fsaM3 = new FuzzySet("aM3", new TrapezoidalFunction(-45, -30, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsaM2 = new FuzzySet("aM2", new TrapezoidalFunction(-45f, -30f, -5f));
FuzzySet fsaM1 = new FuzzySet("aM1", new TrapezoidalFunction(-30f, -17f, -5f));
FuzzySet fsaS = new FuzzySet("aS", new TrapezoidalFunction(-5f, 0, 5f));
FuzzySet fsaD1 = new FuzzySet("aD1", new TrapezoidalFunction(5f, 17f, 30f));
FuzzySet fsaD2 = new FuzzySet("aD2", new TrapezoidalFunction(5f, 30f, 45f));
FuzzySet fsaD3 = new FuzzySet("aD3", new TrapezoidalFunction(30, 45, TrapezoidalFunction.EdgeType.Left));
LinguisticVariable lvA = new LinguisticVariable("OutAngle", -45, 45);
lvA.AddLabel(fsaM3);
lvA.AddLabel(fsaM2);
lvA.AddLabel(fsaM1);
lvA.AddLabel(fsaS);
lvA.AddLabel(fsaD1);
lvA.AddLabel(fsaD2);
lvA.AddLabel(fsaD3);
Database fuzzyDB = new Database();
fuzzyDB.AddVariable(lvX);
fuzzyDB.AddVariable(lvF);
fuzzyDB.AddVariable(lvA);
/*
* float x = -100, F = 180, A = 45;
* float Px = 0, Pf = 0, Pa = 0;
* int Nx = -1, Nf = -1, Na = -1;
*
* float _t = lvX.GetLabelMembership("xM2", x);
* if (_t > Px)
* {
* Px = _t;
* Nx = 0;
* }
*
* _t = lvX.GetLabelMembership("xM1", x);
* if (_t > Px)
* {
* Px = _t;
* Nx = 1;
* }
*
* _t = lvX.GetLabelMembership("xS", x);
* if (_t > Px)
* {
* Px = _t;
* Nx = 2;
* }
*
* _t = lvX.GetLabelMembership("xD1", x);
* if (_t > Px)
* {
* Px = _t;
* Nx = 3;
* }
*
* _t = lvX.GetLabelMembership("xD2", x);
* if (_t > Px)
* {
* Px = _t;
* Nx = 4;
* }*/
InferenceSystem IS = new InferenceSystem(fuzzyDB, new CentroidDefuzzifier(1000));
IS.NewRule("Rule 1", "IF XDist IS xM2 AND FAngle IS fD3 THEN OutAngle IS aD3");
//Rule r = IS.GetRule("Rule 1");
//Clause cl = r.Output;
IS.SetInput("XDist", -100);
IS.SetInput("FAngle", 180);
float fu = lvX.GetLabelMembership("xM2", -100); // 0.29
float fuu = lvF.GetLabelMembership("fD3", 180); // 0.2
float a = IS.Evaluate("OutAngle"); // -> 38.2
try
{
FuzzyOutput fuzzyOutput = IS.ExecuteInference("OutAngle"); // -> 0.2 ad3
foreach (FuzzyOutput.OutputConstraint oc in fuzzyOutput.OutputList)
{
Console.WriteLine(oc.Label + " - " + oc.FiringStrength.ToString());
}
}
catch (Exception)
{
}
}
public FuzzyEngine()
{
// Linguistic labels (fuzzy sets) for Momentum
var momDown = new FuzzySet("Down", new TrapezoidalFunction(-20, 5, 5, 5));
var momNeutral = new FuzzySet("Neutral", new TrapezoidalFunction(-20, 0, 0, 20));
var momUp = new FuzzySet("Up", new TrapezoidalFunction(5, 20, 20, 20));
// Linguistic labels (fuzzy sets) for RSI
var rsiLow = new FuzzySet("Low", new TrapezoidalFunction(0, 30, 30, 30));
var rsiMedium = new FuzzySet("Medium", new TrapezoidalFunction(0, 50, 50, 100));
var rsiHigh = new FuzzySet("High", new TrapezoidalFunction(70, 100, 100, 100));
// MOM (Input)
var lvMom = new LinguisticVariable("MOM", -20, 20);
lvMom.AddLabel(momDown);
lvMom.AddLabel(momNeutral);
lvMom.AddLabel(momUp);
// RSI (Input)
var lvRsi = new LinguisticVariable("RSI", 0, 100);
lvRsi.AddLabel(rsiLow);
lvRsi.AddLabel(rsiMedium);
lvRsi.AddLabel(rsiHigh);
// Linguistic labels (fuzzy sets) that compose the Signal
var fsShort = new FuzzySet("Sell", new TrapezoidalFunction(-100, 0, 0, 00));
var fsHold = new FuzzySet("Hold", new TrapezoidalFunction(-50, 0, 0, 50));
var fsLong = new FuzzySet("Buy", new TrapezoidalFunction(0, 100, 100, 100));
// Output
var lvSignal = new LinguisticVariable("Signal", -100, 100);
lvSignal.AddLabel(fsShort);
lvSignal.AddLabel(fsHold);
lvSignal.AddLabel(fsLong);
// The database
var fuzzyDB = new Database();
fuzzyDB.AddVariable(lvMom);
fuzzyDB.AddVariable(lvRsi);
fuzzyDB.AddVariable(lvSignal);
// Creating the inference system
IS = new InferenceSystem(fuzzyDB, new CentroidDefuzzifier(1000));
// Rules
IS.NewRule("Rule 1", "IF RSI IS Low AND MOM IS Down THEN Signal IS Buy");
IS.NewRule("Rule 2", "IF RSI IS Medium AND MOM IS Down THEN Signal IS Buy");
IS.NewRule("Rule 3", "IF RSI IS High AND MOM IS Down THEN Signal IS Hold");
IS.NewRule("Rule 4", "IF RSI IS Low AND MOM IS Neutral THEN Signal IS Buy");
IS.NewRule("Rule 5", "IF RSI IS Medium AND MOM IS Neutral THEN Signal IS Hold");
IS.NewRule("Rule 6", "IF RSI IS High AND MOM IS Neutral THEN Signal IS Sell");
IS.NewRule("Rule 7", "IF RSI IS Low AND MOM IS Up THEN Signal IS Hold");
IS.NewRule("Rule 8", "IF RSI IS Medium AND MOM IS Up THEN Signal IS Sell");
IS.NewRule("Rule 9", "IF RSI IS High AND MOM IS Up THEN Signal IS Sell");
}
private void BuildInferenceSystem()
{
#region Add linguistic variables
// Input
var lvDistance = GetDistanceVariable();
var lvDate = GetDateVariable();
// Output
var lvSeismicEnv = GetSeismicityVariable("Seismicity");
var lvWeekSeismicEnv = GetSeismicityVariable("WeekSeismicity");
var lvMonthSeismicEnv = GetSeismicityVariable("MonthSeismicity");
// Input Calculated average earthquake concetration (near only)
var lvWeekConcentration = GetConcentrationVariable("WeekConcentration", StartDate.AddDays(-7), StartDate);
var lvTwoWeeksConcentration = GetConcentrationVariable("TwoWeeksConcentration", StartDate.AddDays(-14), StartDate.AddDays(-7));
var lvFiveYearsConcentration = GetConcentrationVariable("FiveYearsConcentration", StartDate.AddYears(-5), StartDate.AddDays(-14));
var lvTenYearsConcentration = GetConcentrationVariable("TenYearsConcentration", StartDate.AddYears(-10), StartDate.AddYears(-5));
var lvFiftyYearsConcentration = GetConcentrationVariable("FiftyYearsConcentration", StartDate.AddYears(-50), StartDate.AddYears(-10));
var lvCenturyConcentration = GetConcentrationVariable("CenturyConcentration", StartDate.AddYears(-100), StartDate.AddYears(-50));
// Input Calculated maximum earthquake magnitude
var lvMaxWeekMagnitude = GetMagnitudeVariable("MaxWeekMagnitude");
var lvMaxTwoWeeksMagnitude = GetMagnitudeVariable("MaxTwoWeeksMagnitude");
var lvMaxFiveYearsMagnitude = GetMagnitudeVariable("MaxFiveYearsMagnitude");
var lvMaxTenYearsMagnitude = GetMagnitudeVariable("MaxTenYearsMagnitude");
var lvMaxFiftyYearsMagnitude = GetMagnitudeVariable("MaxFiftyYearsMagnitude");
var lvMaxCenturyMagnitude = GetMagnitudeVariable("MaxCenturyMagnitude");
// Input Calculated biggest earthquake depth
var lvMaxWeekDepth = GetDepthVariable("MaxWeekDepth");
var lvMaxTwoWeeksDepth = GetDepthVariable("MaxTwoWeeksDepth");
var lvMaxFiveYearsDepth = GetDepthVariable("MaxFiveYearsDepth");
var lvMaxTenYearsDepth = GetDepthVariable("MaxTenYearsDepth");
var lvMaxFiftyYearsDepth = GetDepthVariable("MaxFiftyYearsDepth");
var lvMaxCenturyDepth = GetDepthVariable("MaxCenturyDepth");
Database fuzzyDB = new Database();
fuzzyDB.AddVariable(lvDistance);
fuzzyDB.AddVariable(lvDate);
fuzzyDB.AddVariable(lvSeismicEnv);
fuzzyDB.AddVariable(lvWeekSeismicEnv);
fuzzyDB.AddVariable(lvMonthSeismicEnv);
fuzzyDB.AddVariable(lvWeekConcentration);
fuzzyDB.AddVariable(lvTwoWeeksConcentration);
fuzzyDB.AddVariable(lvFiveYearsConcentration);
fuzzyDB.AddVariable(lvTenYearsConcentration);
fuzzyDB.AddVariable(lvFiftyYearsConcentration);
fuzzyDB.AddVariable(lvCenturyConcentration);
fuzzyDB.AddVariable(lvMaxWeekMagnitude);
fuzzyDB.AddVariable(lvMaxTwoWeeksMagnitude);
fuzzyDB.AddVariable(lvMaxFiveYearsMagnitude);
fuzzyDB.AddVariable(lvMaxTenYearsMagnitude);
fuzzyDB.AddVariable(lvMaxFiftyYearsMagnitude);
fuzzyDB.AddVariable(lvMaxCenturyMagnitude);
fuzzyDB.AddVariable(lvMaxWeekDepth);
fuzzyDB.AddVariable(lvMaxTwoWeeksDepth);
fuzzyDB.AddVariable(lvMaxFiveYearsDepth);
fuzzyDB.AddVariable(lvMaxTenYearsDepth);
fuzzyDB.AddVariable(lvMaxFiftyYearsDepth);
fuzzyDB.AddVariable(lvMaxCenturyDepth);
#endregion
quakeSystem = new InferenceSystem(fuzzyDB, new CentroidDefuzzifier(1000), new MinimumNorm(), new MaximumCoNorm());
#region Construct rules
// Current seismicity rules
string nearAndSoonClause = "Distance IS Near AND (Date IS Week OR Date IS TwoWeeks)";
string tooStrongMagnitudeClause = "(MaxWeekMagnitude IS Great OR MaxWeekMagnitude IS Major)";
string strongMagnitudeClause = "MaxWeekMagnitude IS Strong";
string moderateMagnitudeClause = "MaxWeekMagnitude IS Moderate";
string lightMagnitudeClause = "MaxWeekMagnitude IS Light";
string belowLightMagnitudeClause = "(MaxWeekMagnitude IS Light OR MaxWeekMagnitude IS Minor OR MaxWeekMagnitude IS Micro)";
string shallowDepthClause = "MaxWeekDepth IS Shallow";
string notShallowDepthClause = "MaxWeekDepth IS NOT Shallow";
string fairlyDeepClause = "(MaxWeekDepth IS Fairly OR MaxWeekDepth is Deep)";
string veryDeepClause = "MaxWeekDepth IS VeryDeep";
// near events
rules.Add(quakeSystem.NewRule("Rule 1", "IF " + nearAndSoonClause +
" AND " + tooStrongMagnitudeClause + " THEN Seismicity IS Great"));
rules.Add(quakeSystem.NewRule("Rule 2", "IF " + nearAndSoonClause +
" AND " + strongMagnitudeClause + " AND " + shallowDepthClause + " THEN Seismicity is Great"));
rules.Add(quakeSystem.NewRule("Rule 3", "IF " + nearAndSoonClause +
" AND " + strongMagnitudeClause + " AND " + fairlyDeepClause + " THEN Seismicity is Strong"));
rules.Add(quakeSystem.NewRule("Rule 4", "IF " + nearAndSoonClause +
" AND " + strongMagnitudeClause + " AND " + veryDeepClause + " THEN Seismicity is Strong"));
rules.Add(quakeSystem.NewRule("Rule 5", "IF " + nearAndSoonClause +
" AND " + moderateMagnitudeClause + " AND " + shallowDepthClause + " THEN Seismicity is Strong"));
rules.Add(quakeSystem.NewRule("Rule 6", "IF " + nearAndSoonClause +
" AND " + moderateMagnitudeClause + " AND " + notShallowDepthClause + " THEN Seismicity is Medium"));
rules.Add(quakeSystem.NewRule("Rule 7", "IF " + nearAndSoonClause +
" AND " + lightMagnitudeClause + " AND " + shallowDepthClause + " THEN Seismicity is Medium"));
rules.Add(quakeSystem.NewRule("Rule 8", "IF " + nearAndSoonClause +
" AND " + belowLightMagnitudeClause + " AND " + notShallowDepthClause + " THEN Seismicity is Low"));
// far events
string fairAndSoonClause = "Distance IS Fair AND (Date IS Week OR Date is TwoWeeks)";
rules.Add(quakeSystem.NewRule("Rule 9", "IF " + fairAndSoonClause + " AND " +
tooStrongMagnitudeClause + " THEN Seismicity IS Great"));
rules.Add(quakeSystem.NewRule("Rule 10", "IF " + fairAndSoonClause + " AND " + strongMagnitudeClause +
" AND " + shallowDepthClause + " THEN Seismicity IS Strong"));
rules.Add(quakeSystem.NewRule("Rule 11", "IF " + fairAndSoonClause + " AND " + strongMagnitudeClause +
" AND " + fairlyDeepClause + " THEN Seismicity IS Strong"));
rules.Add(quakeSystem.NewRule("Rule 12", "IF " + fairAndSoonClause + " AND " + strongMagnitudeClause +
" AND " + veryDeepClause + " THEN Seismicity IS Medium"));
rules.Add(quakeSystem.NewRule("Rule 13", "IF " + fairAndSoonClause + " AND " + moderateMagnitudeClause +
" AND " + shallowDepthClause + " THEN Seismicity IS Medium"));
rules.Add(quakeSystem.NewRule("Rule 14", "IF " + fairAndSoonClause + " AND " + moderateMagnitudeClause +
" AND " + notShallowDepthClause + " THEN Seismicity IS Low"));
rules.Add(quakeSystem.NewRule("Rule 15", "IF " + fairAndSoonClause + " AND " +
"(" + lightMagnitudeClause + " OR " + belowLightMagnitudeClause + ")" +
" THEN Seismicity IS Low"));
// Predict next week - subsiding
string soonClause = "(Date IS Week OR Date IS TwoWeeks)";
rules.Add(quakeSystem.NewRule("Rule 16", "IF " + soonClause + " AND (WeekConcentration IS Big OR TwoWeeksConcentration IS Big) " +
"AND (MaxWeekMagnitude IS Great OR MaxTwoWeeksMagnitude IS Great OR " +
"MaxWeekMagnitude IS Major OR MaxTwoWeeksMagnitude IS Major)" +
" THEN WeekSeismicity IS Strong"));
rules.Add(quakeSystem.NewRule("Rule 17", "IF " + soonClause + " AND (WeekConcentration IS Big OR TwoWeeksConcentration IS Big) " +
"AND (MaxWeekMagnitude IS Strong OR MaxTwoWeeksMagnitude IS Strong OR " +
"MaxWeekMagnitude IS Moderate OR MaxTwoWeeksMagnitude IS Moderate)" +
" THEN WeekSeismicity IS Medium"));
rules.Add(quakeSystem.NewRule("Rule 18", "IF " + soonClause + " AND (WeekConcentration IS Big OR TwoWeeksConcentration IS Big) " +
"AND (MaxWeekMagnitude IS Light OR MaxTwoWeeksMagnitude IS Light OR " +
"MaxWeekMagnitude IS Minor OR MaxTwoWeeksMagnitude IS Minor OR " +
"MaxWeekMagnitude IS Micro OR MaxTwoWeeksMagnitude IS Micro)" +
" THEN WeekSeismicity IS Low"));
// Predict next month
string upToMonthClause = "(Date IS Week OR Date IS TwoWeeks OR Date IS Month)";
rules.Add(quakeSystem.NewRule("Rule 19", "IF " + upToMonthClause + " AND FiveYearsConcentration IS Medium AND TenYearsConcentration IS Medium " +
"AND (MaxFiveYearsMagnitude IS Strong AND MaxTenYearsMagnitude IS Strong OR " +
"MaxFiveYearsMagnitude IS Moderate AND MaxTenYearsMagnitude IS Moderate)" +
" THEN MonthSeismicity IS Strong"));
rules.Add(quakeSystem.NewRule("Rule 20", "IF " + upToMonthClause + " AND FiveYearsConcentration IS Medium AND TenYearsConcentration IS Medium " +
"AND MaxFiveYearsMagnitude IS Light AND MaxTenYearsMagnitude IS Light" +
" THEN MonthSeismicity IS Medium"));
rules.Add(quakeSystem.NewRule("Rule 21", "IF " + upToMonthClause + " AND FiveYearsConcentration IS Medium AND TenYearsConcentration IS Medium " +
"AND (MaxFiveYearsMagnitude IS Minor OR MaxFiveYearsMagnitude IS Micro) AND " +
"(MaxTenYearsMagnitude IS Minor OR MaxTenYearsMagnitude IS Micro)" +
" THEN MonthSeismicity IS Low"));
string upToYearClause = "(Date IS Week OR Date IS TwoWeeks OR Date IS Month OR " +
"Date IS ThreeMonths OR Date IS SixMonths OR Date IS Year)";
rules.Add(quakeSystem.NewRule("Rule 22", "IF " + upToYearClause + " AND FiftyYearsConcentration IS Small AND CenturyConcentration IS Small " +
"AND (MaxFiftyYearsMagnitude IS Great AND MaxCenturyMagnitude IS Great OR " +
"MaxFiftyYearsMagnitude IS Major AND MaxCenturyMagnitude IS Major)" +
" THEN MonthSeismicity IS Great"));
rules.Add(quakeSystem.NewRule("Rule 23", "IF " + upToYearClause +
" AND NOT (MaxFiftyYearsMagnitude IS Great AND MaxCenturyMagnitude IS Great OR " +
"MaxFiftyYearsMagnitude IS Major AND MaxCenturyMagnitude IS Major)" +
" THEN MonthSeismicity IS Low"));
#endregion
}
void InitEvenly()
{
const int numTerms = 10;
const float cross = 1.8f;
RMS0 = new LingVar("rms0", numTerms, 0.4f / 10000f, 23f / 10000f, cross);
RMS1 = new LingVar("rms1", numTerms, 0.4f / 10000f, 23f / 10000f, cross);
Deviation0 = new LingVar("deviation0", numTerms, 0.5f / 10000f, 34.26f / 10000f, cross);
Deviation1 = new LingVar("deviation1", numTerms, 0.5f / 10000f, 34.26f / 10000f, cross);
Turns0 = new LingVar("turns0", numTerms, 0, 175, cross);
Turns1 = new LingVar("turns1", numTerms, 0, 175, cross);
Zeros0 = new LingVar("zeros0", numTerms, 14, 80, cross);
Zeros1 = new LingVar("zeros1", numTerms, 14, 80, cross);
deltaRMS = new LingVar("deltarms", numTerms, -12.5f, 20.8f, cross);
const int numOutTerms = 10;
output = new LingVar("out", numOutTerms, 1, numOutTerms, 1.3f);
fuzzyDB = new Database();
//fuzzyDB.AddVariable(RMS1.lv);
//fuzzyDB.AddVariable(RMS2.lv);
//fuzzyDB.AddVariable(Deviation1.lv);
//fuzzyDB.AddVariable(Deviation2.lv);
fuzzyDB.AddVariable(Turns0.lv);
fuzzyDB.AddVariable(Turns1.lv);
fuzzyDB.AddVariable(Zeros0.lv);
fuzzyDB.AddVariable(Zeros1.lv);
fuzzyDB.AddVariable(deltaRMS.lv);
fuzzyDB.AddVariable(output.lv);
RulesCalc = new List <float> [numTerms, numTerms, numTerms, numTerms, numTerms][];
Rules = new int[numTerms, numTerms, numTerms, numTerms, numTerms];
for (int q = 0; q < numTerms; q++)
{
for (int w = 0; w < numTerms; w++)
{
for (int e = 0; e < numTerms; e++)
{
for (int r = 0; r < numTerms; r++)
{
for (int t = 0; t < numTerms; t++)
{
RulesCalc[q, w, e, r, t] = new List <float>[numOutTerms] {
new List <float>(), new List <float>(), new List <float>(), new List <float>(), new List <float>(), new List <float>(), new List <float>(), new List <float>(), new List <float>(), new List <float>()
};
Rules[q, w, e, r, t] = 0;
}
}
}
}
}
loadData();
for (int q = 0; q < numTerms; q++)
{
for (int w = 0; w < numTerms; w++)
{
for (int e = 0; e < numTerms; e++)
{
for (int r = 0; r < numTerms; r++)
{
for (int t = 0; t < numTerms; t++)
{
float[] average = new float[numOutTerms]; // среднее арифметическое
for (int i = 0; i < numOutTerms; i++) // количество листов (столбцов с цифрами) / количество выходных термов
{
int count = RulesCalc[q, w, e, r, t][i].Count; // количество цифр в столбце
if (count == 0) // если столбец пуст
{
average[i] = 0;
}
else // если в столбце что-то есть
{
average[i] = RulesCalc[q, w, e, r, t][i].Average();
}
}
// посчитали среднее для всех столбцов, можно выбирать правило
float _t = average.Max();
if (_t != 0)
{
Rules[q, w, e, r, t] = Array.IndexOf(average, _t) + 1;
}
else
{
Rules[q, w, e, r, t] = 0;
}
}
}
}
}
}
#region Заполнение нулевых ячеек таблицы правил
//bool zers = true, zer = false;
//double countenv = (Math.Pow(3, 5) - 1);
//float div = 2f;
//int ZEROSAAAAA1 = 0;
//int ZEROSAAAAA2 = 0;
//while (zers)
//{
// ZEROSAAAAA1 = 0;
// for (int q = 0; q < numTerms; q++)
// for (int w = 0; w < numTerms; w++)
// for (int e = 0; e < numTerms; e++)
// for (int r = 0; r < numTerms; r++)
// for (int t = 0; t < numTerms; t++)
// {
// if (Rules[q, w, e, r, t] == 0)
// {
// ZEROSAAAAA1++;
// int[] environs = new int[numOutTerms];
// int notclass = 0, inclass = 0;
// int outofrange = 0;
// zer = true;
// int fuu = 0;
// for (int a = -1; a <= 1; a++)
// for (int s = -1; s <= 1; s++)
// for (int d = -1; d <= 1; d++)
// for (int f = -1; f <= 1; f++)
// for (int g = -1; g <= 1; g++)
// {
// if ((q + a >= 0 && w + s >= 0 && e + d >= 0 && r + f >= 0 && t + g >= 0) &&
// (q + a < numTerms && w + s < numTerms && e + d < numTerms && r + f < numTerms && t + g < numTerms))
// {
// if (!(q == a && w == s && e == d && r == f && t == g))
// {
// if (Rules[q + a, w + s, e + d, r + f, t + g] == 0)
// notclass++;
// else
// {
// environs[Rules[q + a, w + s, e + d, r + f, t + g] - 1]++;
// inclass++;
// }
// }
// }
// else
// {
// int fu = 0;
// if ((q + a < 0) || (q + a >= numTerms))
// {
// fu++;
// }
// if ((w + s < 0) || (w + s >= numTerms))
// {
// fu++;
// }
// if ((e + d < 0) || (e + d >= numTerms))
// {
// fu++;
// }
// if ((r + f < 0) || (r + f >= numTerms))
// {
// fu++;
// }
// if ((t + g < 0) || (t + g >= numTerms))
// {
// fu++;
// }
// if (fu > fuu) fuu = fu;
// outofrange++;
// }
// }
// int max = environs.Max();
// if ((fuu == 0) && (max != 0))
// {
// if (inclass > 242f / div)
// {
// Rules[q, w, e, r, t] = Array.IndexOf(environs, max) + 1;
// }
// }
// else if (fuu == 1)
// {
// if (inclass > 161f / div)
// {
// Rules[q, w, e, r, t] = Array.IndexOf(environs, max) + 1;
// }
// }
// else if (fuu == 2)
// {
// if (notclass > 107f / div)
// {
// Rules[q, w, e, r, t] = Array.IndexOf(environs, max) + 1;
// }
// }
// else if (fuu == 3)
// {
// if (notclass > 71f / div)
// {
// Rules[q, w, e, r, t] = Array.IndexOf(environs, max) + 1;
// }
// }
// else if (fuu == 4)
// {
// if (notclass > 47f / div)
// {
// Rules[q, w, e, r, t] = Array.IndexOf(environs, max) + 1;
// }
// }
// else if (fuu == 5)
// {
// if (notclass > 31f / div)
// {
// Rules[q, w, e, r, t] = Array.IndexOf(environs, max) + 1;
// }
// }
// }
// }
// if (!zer) zers = false;
// zer = false;
// if (ZEROSAAAAA1 == ZEROSAAAAA2)
// zers = false;
// else
// ZEROSAAAAA2 = ZEROSAAAAA1;
// Console.WriteLine(ZEROSAAAAA1);
//}
#endregion
#region Оптимизация правил
//RulesOptimizer[] rulOpt = new RulesOptimizer[numOutTerms];
//for (int i = 0; i < rulOpt.Length; i++)
//{
// rulOpt[i] = new RulesOptimizer();
//}
//for (int q = 0; q < numTerms; q++)
// for (int w = 0; w < numTerms; w++)
// for (int e = 0; e < numTerms; e++)
// for (int r = 0; r < numTerms; r++)
// for (int t = 0; t < numTerms; t++)
// {
// if (Rules[q, w, e, r, t] != 0)
// {
// rulOpt[Rules[q, w, e, r, t] - 1].addRule(q, w, e, r, t);
// }
// }
//foreach (var item in rulOpt)
//{
// item.optimize();
//}
#endregion
/* Формат правил
*
* лист
* \/
* Прi = | 1 | 1 | 1 | 2 | 1 | <- массив листов
* | 5 | 3 | | 4 | |
* | | 6 | | | |
*
* rules[i] - List<int>[]
* rules[i][k] - List<int>
* rules[i][k][n] - int
*/
IS = new InferenceSystem(fuzzyDB, new CentroidDefuzzifier(CentrDefu));
string rule;
for (int q = 0; q < numTerms; q++)
{
for (int w = 0; w < numTerms; w++)
{
for (int e = 0; e < numTerms; e++)
{
for (int r = 0; r < numTerms; r++)
{
for (int t = 0; t < numTerms; t++)
{
if (Rules[q, w, e, r, t] != 0)
{
rule = "";
rule += "IF turns0 IS " + Turns0.terms[q].Name;
rule += " AND turns1 IS " + Turns1.terms[w].Name;
rule += " AND zeros0 IS " + Zeros0.terms[e].Name;
rule += " AND zeros1 IS " + Zeros1.terms[r].Name;
rule += " AND deltarms IS " + deltaRMS.terms[t].Name;
rule += " THEN out IS " + output.terms[Rules[q, w, e, r, t] - 1].Name;
IS.NewRule(q.ToString() + w.ToString() + e.ToString() + r.ToString() + t.ToString(), rule);
}
}
}
}
}
}
#region Тестирование для оптимизации
//string rule = "";
//for (int q = 0; q < rulOpt.Length; q++) // перечисляет выходы от 0 до 9
//{
// for (int w = 0; w < rulOpt[q].Rules.Count; w++) // перебирает правила для каждого выхода
// {
// Clause[][] clauses = new Clause[rulOpt[q].Rules[w].Length][]; // размерность 5 х N
// for (int e = 0; e < rulOpt[q].Rules[w].Length; e++) // от 0 до 4 перебирает лингвистические переменные
// {
// clauses[e] = new Clause[rulOpt[q].Rules[w][e].Count]; // кол-во клауз = кол-ву вариантов значений лингвистических переменных
// for (int r = 0; r < clauses[e].Length; r++)
// {
// int itemp = rulOpt[q].Rules[w][e][r];
// switch (e)
// {
// case 0:
// clauses[e][r] = new Clause(Turns0.lv, Turns0.terms[itemp]);
// break;
// case 1:
// clauses[e][r] = new Clause(Turns1.lv, Turns1.terms[itemp]);
// break;
// case 2:
// clauses[e][r] = new Clause(Zeros0.lv, Zeros0.terms[itemp]);
// break;
// case 3:
// clauses[e][r] = new Clause(Zeros1.lv, Zeros1.terms[itemp]);
// break;
// case 4:
// clauses[e][r] = new Clause(deltaRMS.lv, deltaRMS.terms[itemp]);
// break;
// }
// }
// }
// rule = "IF ";
// string temp;
// for (int e = 0; e < clauses.Length; e++)
// {
// temp = "(";
// for (int r = 0; r < clauses[e].Length - 1; r++)
// {
// temp += clauses[e][r] + " OR ";
// }
// temp += clauses[e][clauses[e].Length - 1] + ")";
// if (e == clauses.Length - 1)
// rule += temp;
// else
// rule += temp + " AND ";
// }
// rule += " THEN out IS " + output.terms[q].Name;
// //rule += "IF turns0 IS " + Turns0.terms[q].Name;
// //rule += " AND turns1 IS " + Turns1.terms[w].Name;
// //rule += " AND zeros0 IS " + Zeros0.terms[e].Name;
// //rule += " AND zeros1 IS " + Zeros1.terms[r].Name;
// //rule += " AND deltarms IS " + deltaRMS.terms[t].Name;
// //rule += " THEN out IS " + output.terms[Rules[q, w, e, r, t] - 1].Name;
// IS.NewRule(q.ToString() + w.ToString(), rule);
// }
//}
#endregion
}
void InitFuzzyEngine()
{
//Sunciones de Pertenencia
//Alturas
FuzzySet fsBaja = new FuzzySet("Baja", new TrapezoidalFunction(-1f, 0f, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsMedia = new FuzzySet("Media", new TrapezoidalFunction(-1f, -0.1f, 0.1f, 1f));
FuzzySet fsAlta = new FuzzySet("Alta", new TrapezoidalFunction(0f, 1f, TrapezoidalFunction.EdgeType.Left));
//Velocidades
FuzzySet fsMn = new FuzzySet("Negativa", new TrapezoidalFunction(-1f, -0.5f, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsZero = new FuzzySet("Media", new TrapezoidalFunction(-1f, -0.5f, 0.5f, 1f));
FuzzySet fsMp = new FuzzySet("Positiva", new TrapezoidalFunction(0.5f, 1f, TrapezoidalFunction.EdgeType.Left));
//Fuerzas
FuzzySet fsZf = new FuzzySet("PocaFuerza", new TrapezoidalFunction(0f, 1f, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsPf = new FuzzySet("ZeroFuerza", new TrapezoidalFunction(0.5f, 1f, 9f, 10f));
FuzzySet fsMf = new FuzzySet("MuchaFuerza", new TrapezoidalFunction(9.5f, 16f, TrapezoidalFunction.EdgeType.Left));
//Entradas
//Altura
LinguisticVariable lvAltura = new LinguisticVariable("Altura", -15, 15);
lvAltura.AddLabel(fsBaja);
lvAltura.AddLabel(fsMedia);
lvAltura.AddLabel(fsAlta);
//Velocidades
LinguisticVariable lvVelocidad = new LinguisticVariable("Velocidad", -25, 25);
lvVelocidad.AddLabel(fsMn);
lvVelocidad.AddLabel(fsZero);
lvVelocidad.AddLabel(fsMp);
//Fuerzas
LinguisticVariable lvFuerza = new LinguisticVariable("Fuerza", 0, 16);
lvFuerza.AddLabel(fsPf);
lvFuerza.AddLabel(fsZf);
lvFuerza.AddLabel(fsMf);
//La base de datos
Database fuzzyDb = new Database();
fuzzyDb.AddVariable(lvAltura);
fuzzyDb.AddVariable(lvFuerza);
fuzzyDb.AddVariable(lvVelocidad);
//Sistema de interferencia
ISL = new InferenceSystem(fuzzyDb, new CentroidDefuzzifier(1000));
ISL.NewRule("Rule 1", "IF Altura IS Baja AND Velocidad IS Negativa THEN Fuerza IS MuchaFuerza");
ISL.NewRule("Rule 2", "IF Altura IS Baja AND Velocidad IS Media THEN Fuerza IS MuchaFuerza");
ISL.NewRule("Rule 3", "IF Altura IS Baja AND Velocidad IS Positiva THEN Fuerza IS MuchaFuerza");
ISL.NewRule("Rule 4", "IF Altura IS Media AND Velocidad IS Negativa THEN Fuerza IS MuchaFuerza");
ISL.NewRule("Rule 5", "IF Altura IS Media AND Velocidad IS Media THEN Fuerza IS ZeroFuerza");
ISL.NewRule("Rule 6", "IF Altura IS Media AND Velocidad IS Positiva THEN Fuerza IS ZeroFuerza");
ISL.NewRule("Rule 7", "IF Altura IS Alta AND Velocidad IS Negativa THEN Fuerza IS ZeroFuerza");
ISL.NewRule("Rule 8", "IF Altura IS Alta AND Velocidad IS Media THEN Fuerza IS ZeroFuerza");
ISL.NewRule("Rule 9", "IF Altura IS Alta AND Velocidad IS Positiva THEN Fuerza IS ZeroFuerza");
}
void loadData()
{
openFileDialog1.InitialDirectory = @"D:\YandexDisk\Программирование\GestureRecognize\GestureRecognize\bin\Debug";
if (openFileDialog1.ShowDialog() == DialogResult.OK)
{
BinaryFormatter bf = new BinaryFormatter();
using (FileStream fs = File.OpenRead(openFileDialog1.FileName))
{
data = (Data[, ])bf.Deserialize(fs);
}
}
int numFeatures = 5, _num, k, numSamples = 5000;
double threshold = 1.3d; // пороговое значение для отношения амплитуд
int width = data[nums[0], 0].X.Count;
int[] addr = new int[numFeatures];
string[] forRule = new string[numFeatures + 1];
for (int n = 0; n < nums.Length; n++)
{
k = nums[n];
for (int i = 0; i < numSamples; i++)
{
_num = 700 + ((width - 700 - 300) / numSamples) * i; // перебор точек 700 - 20000
double r0 = data[k, 0].RMS[_num], r1 = data[k, 1].RMS[_num], dr;
if ((r0 >= r1) && (r0 / r1 >= threshold))
{
dr = r0 / r1;
}
else if ((r0 < r1) && (r1 / r0 >= threshold))
{
dr = -r1 / r0;
}
else
{
dr = 0;
}
//dr = r0 / r1;
forRule[0] = chooseTerm(data[k, 0].Turns[_num], Turns0);
forRule[1] = chooseTerm(data[k, 1].Turns[_num], Turns1);
forRule[2] = chooseTerm(data[k, 0].ZeroCrossings[_num], Zeros0);
forRule[3] = chooseTerm(data[k, 1].ZeroCrossings[_num], Zeros1);
forRule[4] = chooseTerm(dr, deltaRMS);
forRule[5] = chooseTerm(n + 1, output);
IS = new InferenceSystem(fuzzyDB, new CentroidDefuzzifier(CentrDefu));
string rule = "";
rule += "IF turns0 IS " + forRule[0];
rule += " AND turns1 IS " + forRule[1];
rule += " AND zeros0 IS " + forRule[2];
rule += " AND zeros1 IS " + forRule[3];
rule += " AND deltarms IS " + forRule[4];
rule += " THEN out IS " + forRule[5];
IS.NewRule("test", rule);
IS.SetInput(Turns0.lv.Name, data[k, 0].Turns[_num]);
IS.SetInput(Turns1.lv.Name, data[k, 1].Turns[_num]);
IS.SetInput(Zeros0.lv.Name, data[k, 0].ZeroCrossings[_num]);
IS.SetInput(Zeros1.lv.Name, data[k, 1].ZeroCrossings[_num]);
IS.SetInput(deltaRMS.lv.Name, (float)dr);
FuzzyOutput fuzzyOutput = IS.ExecuteInference("out");
for (int j = 0; j < addr.Length; j++)
{
addr[j] = int.Parse(forRule[j].Substring(forRule[j].Length - 1));
}
RulesCalc[addr[0], addr[1], addr[2], addr[3], addr[4]][n].Add(fuzzyOutput.OutputList[0].FiringStrength);
}
}
}
/// <summary>
/// Premier traitement en logique flou permettant d'obtenir les variables Valence et Arousal pour toute liste mesurée
/// </summary>
/// <param name="EMG"></param>
/// <param name="ECG"></param>
/// <param name="EDA"></param>
public void ToValenceAndArousal(List <double> EMG, List <double> ECG, List <double> EDA, List <double> Valence, List <double> Arousal)
{
ResLogFlou1Label.Text = "Traitement en cours";
ResLogFlou1Label.Refresh();
//Pour traitement adapté à chaque signal
int meanEMG = Mean(EMG);
int meanHR = Mean(ECG);
int meanGSR = Mean(EDA);
int sEMG = (int)Math.Sqrt(Var(EMG));
int sHR = (int)Math.Sqrt(Var(ECG));
int sGSR = (int)Math.Sqrt(Var(EDA));
#region Input (EMG)
var lvEMG = new LinguisticVariable("EMG", meanEMG - 10 * sEMG, meanEMG + 10 * sEMG);
var fsLowEMG = new FuzzySet("Low", new TrapezoidalFunction(meanEMG - 10 * sEMG, meanEMG - 5 * sEMG, meanEMG - 2 * sEMG));
var fsMidEMG = new FuzzySet("Mid", new TrapezoidalFunction(meanEMG - 2 * sEMG, meanEMG, meanEMG + 2 * sEMG));
var fsHighEMG = new FuzzySet("High", new TrapezoidalFunction(meanEMG + 2 * sEMG, meanEMG + 5 * sEMG, meanEMG + 10 * sEMG));
lvEMG.AddLabel(fsLowEMG);
lvEMG.AddLabel(fsMidEMG);
lvEMG.AddLabel(fsHighEMG);
#endregion
#region Input (EDA/GSR)
var lvGSR = new LinguisticVariable("GSR", meanGSR - 10 * sGSR, meanGSR + 10 * sGSR);
var fsLowGSR = new FuzzySet("Low", new TrapezoidalFunction(meanGSR - 10 * sGSR, meanGSR - 5 * sGSR, meanGSR - 2 * sGSR));
var fsMidLowGSR = new FuzzySet("MidLow", new TrapezoidalFunction(meanGSR - 2 * sGSR, meanGSR, meanGSR + 2 * sGSR));
var fsMidGSR = new FuzzySet("Mid", new TrapezoidalFunction(meanGSR - 2 * sGSR, meanGSR, meanGSR + 2 * sGSR));
var fsMidHighGSR = new FuzzySet("MidHigh", new TrapezoidalFunction(meanGSR - 2 * sGSR, meanGSR, meanGSR + 2 * sGSR));
var fsHighGSR = new FuzzySet("High", new TrapezoidalFunction(meanGSR - 2 * sGSR, meanGSR, meanGSR + 10 * sGSR));
lvGSR.AddLabel(fsLowGSR);
lvGSR.AddLabel(fsMidLowGSR);
lvGSR.AddLabel(fsMidGSR);
lvGSR.AddLabel(fsMidHighGSR);
lvGSR.AddLabel(fsHighGSR);
#endregion
#region Input (ECG/HR)
var lvHR = new LinguisticVariable("HR", meanHR - 10 * sHR, meanHR + 10 * sHR);
var fsLowHR = new FuzzySet("Low", new TrapezoidalFunction(meanHR - 10 * sHR, meanHR - 5 * sHR, meanHR - 2 * sHR));
var fsMidHR = new FuzzySet("Mid", new TrapezoidalFunction(meanHR - 2 * sHR, meanHR, meanHR + 2 * sHR));
var fsHighHR = new FuzzySet("High", new TrapezoidalFunction(meanHR + 2 * sHR, meanHR + 5 * sHR, meanHR + 10 * sHR));
lvHR.AddLabel(fsLowHR);
lvHR.AddLabel(fsMidHR);
lvHR.AddLabel(fsHighHR);
#endregion
#region Output (Valence)
var lvValence = new LinguisticVariable("Valence", 0, 30);
var fsVeryLow = new FuzzySet("VeryLow", new TrapezoidalFunction(0, 3, 6));
var fsLow = new FuzzySet("Low", new TrapezoidalFunction(6, 7, 8));
var fsMidLow = new FuzzySet("MidLow", new TrapezoidalFunction(8, 9, 10));
var fsMid = new FuzzySet("Mid", new TrapezoidalFunction(10, 15, 20));
var fsMidHigh = new FuzzySet("MidHigh", new TrapezoidalFunction(20, 22, 24));
var fsHigh = new FuzzySet("High", new TrapezoidalFunction(24, 25, 26));
var fsVeryHigh = new FuzzySet("VeryHigh", new TrapezoidalFunction(26, 28, 30));
lvValence.AddLabel(fsVeryLow);
lvValence.AddLabel(fsLow);
lvValence.AddLabel(fsMidLow);
lvValence.AddLabel(fsMid);
lvValence.AddLabel(fsMidHigh);
lvValence.AddLabel(fsHigh);
lvValence.AddLabel(fsVeryHigh);
#endregion
#region Output (Arousal)
var lvArousal = new LinguisticVariable("Arousal", 0, 30);
lvArousal.AddLabel(fsVeryLow);
lvArousal.AddLabel(fsLow);
lvArousal.AddLabel(fsMidLow);
lvArousal.AddLabel(fsMid);
lvArousal.AddLabel(fsMidHigh);
lvArousal.AddLabel(fsHigh);
lvArousal.AddLabel(fsVeryHigh);
#endregion
#region Système Inference
// Base de données pour les variables linguistiques
//Liste des inputs :
// EMG(Low, Mid, High) 0 - 30
// GSR(Low, Mid, High) 0 - 30
// HR (Low, Mid, High) 0 - 30
//Liste des outputs :
// Valence(VeryLow, Low, MidLow, Mid, MidHigh, High, VeryHigh) 0 - 30
// Arousal(VeryLow, Low, MidLow, Mid, MidHigh, High, VeryHigh) 0 - 30
var fuzzyDb = new Database();
fuzzyDb.AddVariable(lvEMG);
fuzzyDb.AddVariable(lvGSR);
fuzzyDb.AddVariable(lvHR);
fuzzyDb.AddVariable(lvValence);
fuzzyDb.AddVariable(lvArousal);
// Creation system inference
// Initialise la methode de défuzzification : centre de gravité
var inferenceSys = new InferenceSystem(fuzzyDb, new CentroidDefuzzifier(1000));
// Ajout des regles
inferenceSys.NewRule("Rule 1", "IF GSR IS High THEN Arousal IS High");
inferenceSys.NewRule("Rule 2", "IF GSR IS MidHigh THEN Arousal IS MidHigh ");
inferenceSys.NewRule("Rule 3", "IF GSR IS MidLow THEN Arousal IS MidLow");
inferenceSys.NewRule("Rule 4", "IF GSR IS Low THEN Arousal IS Low");
inferenceSys.NewRule("Rule 5", "IF HR IS Low THEN Arousal IS Low");
inferenceSys.NewRule("Rule 6", "IF HR IS High THEN Arousal IS High");
inferenceSys.NewRule("Rule 7", "IF GSR IS Low AND HR IS High THEN Arousal IS MidLow");
inferenceSys.NewRule("Rule 8", "IF GSR IS High AND HR IS Low THEN Arousal IS MidHigh");
inferenceSys.NewRule("Rule 9", "IF EMG IS High THEN Valence IS VeryLow");
inferenceSys.NewRule("Rule 10", "IF EMG IS Mid THEN Valence IS Low");
//inferenceSys.NewRule("Rule 11", "IF EMGsmile IS Mid THEN Valence IS High");
//inferenceSys.NewRule("Rule 12", "IF EMGsmile IS High THEN Valence IS very High");
inferenceSys.NewRule("Rule 14", "IF EMG IS Low THEN Valence IS VeryHigh");
inferenceSys.NewRule("Rule 15", "IF EMG IS Mid THEN Valence IS High");
inferenceSys.NewRule("Rule 16", "IF EMG IS High THEN Valence IS VeryLow");
inferenceSys.NewRule("Rule 17", "IF EMG IS High THEN Valence IS Low");
inferenceSys.NewRule("Rule 18", "IF EMG IS Low AND HR IS Low THEN Valence IS Low");
inferenceSys.NewRule("Rule 19", "IF EMG IS Low AND HR IS High THEN Valence IS High");
inferenceSys.NewRule("Rule 20", "IF GSR IS High AND HR IS Mid THEN Arousal IS High");
inferenceSys.NewRule("Rule 21", "IF GSR IS MidHigh AND HR IS Mid THEN Arousal IS MidHigh");
inferenceSys.NewRule("Rule 22", "IF GSR IS MidLow AND HR IS Mid THEN Arousal IS MidLow");
#endregion
#region Exemple
//Pour toutes les valeurs des listes
float valEMG = -1, valGSR = -1, valHR = -1;
for (int i = 0; i < EMG.Count; i++)
{
valEMG = (float)EMG[i];
valGSR = (float)EDA[i];
valHR = (float)ECG[i];
// Initialise les données d'entrées
inferenceSys.SetInput("EMG", valEMG);
inferenceSys.SetInput("GSR", valGSR);
inferenceSys.SetInput("HR", valHR);
// Evalue les données de sortie : Valence, Arousal
var resValence = -1f;
var resArousal = -1f;
try
{
resValence = inferenceSys.Evaluate("Valence");
resArousal = inferenceSys.Evaluate("Arousal");
ResLogFlou1Label.Text = "" + i + "/" + EMG.Count + "_ EMG: " + valEMG + " + GSR: " + valGSR + " + HR: " + valHR + " = Valence: " + resValence + ", Arousal: " + resArousal;
ResLogFlou1Label.Refresh();
//Stockage des résultats dans la liste adéquate au résultat
Valence.Add((double)resValence);
Arousal.Add((double)resArousal);
}
catch (Exception ex)
{
//throw new Exception(string.Format("Erreur : {0}", ex.Message));
Valence.Add(0);
Arousal.Add(0);
}
}
#endregion
}
public static void Main()
{
// linguistic labels (fuzzy sets) that compose the distances
var fsNear = new FuzzySet("Near", new TrapezoidalFunction(
450, 500, TrapezoidalFunction.EdgeType.Left));
var fsMedium = new FuzzySet("Medium", new TrapezoidalFunction(
100, 250, 460, 500));
var fsFar = new FuzzySet("Far", new TrapezoidalFunction(
0, 250, TrapezoidalFunction.EdgeType.Right));
// right Distance (Input)
var lvDist = new LinguisticVariable("Distance", 0, 500);
lvDist.AddLabel(fsNear);
lvDist.AddLabel(fsMedium);
lvDist.AddLabel(fsFar);
// linguistic labels (fuzzy sets) that compose the angle
var fsVeryDownSpeed = new FuzzySet("VeryNegative", new TrapezoidalFunction(
-100, -10, TrapezoidalFunction.EdgeType.Right));
var fsDownSpeed = new FuzzySet("Negative", new TrapezoidalFunction(
-50, -30, -15, -10));
var fsLittleDownSpeed = new FuzzySet("LittleNegative", new TrapezoidalFunction(
-15, -8, -5, -1));
var fsZero = new FuzzySet("Zero", new TrapezoidalFunction(
-10, 0, 5, 10));
var fsLittleUpSpeed = new FuzzySet("LittlePositive", new TrapezoidalFunction(
0, 5, 20, 30));
var fsUpSpeed = new FuzzySet("Positive", new TrapezoidalFunction(
20, 25, 35, 40));
var fsVeryUpSpeed = new FuzzySet("VeryPositive", new TrapezoidalFunction(
35, 100, TrapezoidalFunction.EdgeType.Left));
// angle
var lvSpeed = new LinguisticVariable("Speed", -100, 100);
lvSpeed.AddLabel(fsVeryDownSpeed);
lvSpeed.AddLabel(fsDownSpeed);
lvSpeed.AddLabel(fsLittleDownSpeed);
lvSpeed.AddLabel(fsZero);
lvSpeed.AddLabel(fsLittleUpSpeed);
lvSpeed.AddLabel(fsUpSpeed);
lvSpeed.AddLabel(fsVeryUpSpeed);
// the database
var fuzzyDb = new Database( );
fuzzyDb.AddVariable(lvDist);
fuzzyDb.AddVariable(lvSpeed);
// creating the inference system
var IS = new InferenceSystem(fuzzyDb, new CentroidDefuzzifier(1000));
// going Straight
IS.NewRule("Rule 1", "IF Distance IS Far THEN Speed IS VeryPositive");
// going Straight (if can go anywhere)
IS.NewRule("Rule 2", "IF Distance IS Medium THEN Speed IS Positive");
// near right wall
IS.NewRule("Rule 3", "IF Distance IS Near THEN Speed IS Negative");
// near left wall
IS.SetInput("Distance", 0);
/*try
* {
* double NewSpeed = IS.Evaluate( "Speed" );
* Console.WriteLine("Speed = {0} ", NewSpeed );
* }
* catch ( Exception )
* {
* Console.WriteLine("Speed not s");
* }
* Console.ReadLine();
*/
double curDist = 0;
double newSpeed = 0;
while (curDist < 500)
{
newSpeed = IS.Evaluate("Speed");
curDist += 2 * newSpeed / 3600;
Console.WriteLine("Speed = {0}, position = {1} ", newSpeed, curDist);
IS.SetInput("Distance", (float)(curDist));
//Console.ReadLine();
}
Console.ReadLine();
}
private void Form1_Load(object sender, EventArgs e)
{
// rms
FuzzySet fsLowRMS = new FuzzySet("Low", new TrapezoidalFunction(
(float)RMSmin,
Divide(RMSmin, RMSmax, 3, 1),
TrapezoidalFunction.EdgeType.Right));
FuzzySet fsAverageRMS = new FuzzySet("Average", new TrapezoidalFunction(
(float)RMSmin,
Divide(RMSmin, RMSmax, 3, 1),
Divide(RMSmin, RMSmax, 3, 2),
(float)RMSmax));
FuzzySet fsHighRMS = new FuzzySet("High", new TrapezoidalFunction(
Divide(RMSmin, RMSmax, 3, 2),
(float)RMSmax,
TrapezoidalFunction.EdgeType.Left));
// повороты
FuzzySet fsLowTurns = new FuzzySet("Low", new TrapezoidalFunction(
turnsMin,
Divide(turnsMin, turnsMax, 3, 1),
TrapezoidalFunction.EdgeType.Right));
FuzzySet fsAverageTurns = new FuzzySet("Average", new TrapezoidalFunction(
turnsMin,
Divide(turnsMin, turnsMax, 3, 1),
Divide(turnsMin, turnsMax, 3, 2),
turnsMax));
FuzzySet fsHighTurns = new FuzzySet("High", new TrapezoidalFunction(
Divide(turnsMin, turnsMax, 3, 2),
turnsMax,
TrapezoidalFunction.EdgeType.Left));
LinguisticVariable lvRMS = new LinguisticVariable("RMS", (float)RMSmin, (float)RMSmax);
lvRMS.AddLabel(fsLowRMS);
lvRMS.AddLabel(fsAverageRMS);
lvRMS.AddLabel(fsHighRMS);
LinguisticVariable lvTurns = new LinguisticVariable("Turns", turnsMin, turnsMax);
lvTurns.AddLabel(fsLowTurns);
lvTurns.AddLabel(fsAverageTurns);
lvTurns.AddLabel(fsHighTurns);
// выход
FuzzySet fsСlonus = new FuzzySet("True", new SingletonFunction(1));
FuzzySet fsClonusNot = new FuzzySet("False", new SingletonFunction(0));
LinguisticVariable lvClonus = new LinguisticVariable("Clonus", 0, 1);
lvClonus.AddLabel(fsСlonus);
lvClonus.AddLabel(fsClonusNot);
Database fuzzyDB = new Database();
fuzzyDB.AddVariable(lvClonus);
fuzzyDB.AddVariable(lvRMS);
fuzzyDB.AddVariable(lvTurns);
InferenceSystem IS = new InferenceSystem(fuzzyDB, new CentroidDefuzzifier(1000));
IS.NewRule("Rule 1", "IF RMS IS Low OR Turns IS Low THEN Clonus IS False");
IS.NewRule("Rule 2", "IF RMS IS High AND Turns IS High THEN Clonus IS True");
}
static void Main(string[] args)
{
InferenceSystem IS;
int estatura = 0, simpatia = 0, inteligencia = 0, complexion = 0, tez = 0, bellezaE;
float belleza = 0;
string bellezaR = "";
FuzzySet fsBajo = new FuzzySet("Bajo", new TrapezoidalFunction(140, 155, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsMedio = new FuzzySet("Medio", new TrapezoidalFunction(160, 170, 175));
FuzzySet fsAlto = new FuzzySet("Alto", new TrapezoidalFunction(180, 190, TrapezoidalFunction.EdgeType.Left));
LinguisticVariable lvEstatura = new LinguisticVariable("Estatura", 140, 190);
lvEstatura.AddLabel(fsBajo);
lvEstatura.AddLabel(fsMedio);
lvEstatura.AddLabel(fsAlto);
FuzzySet fsMalGenio = new FuzzySet("MalGenio", new TrapezoidalFunction(0, 3, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsNeutro = new FuzzySet("Neutro", new TrapezoidalFunction(4, 5, 6));
FuzzySet fsAgradable = new FuzzySet("Agradable", new TrapezoidalFunction(7, 10, TrapezoidalFunction.EdgeType.Left));
LinguisticVariable lvSimpatia = new LinguisticVariable("Simpatia", 0, 10);
lvSimpatia.AddLabel(fsMalGenio);
lvSimpatia.AddLabel(fsNeutro);
lvSimpatia.AddLabel(fsAgradable);
FuzzySet fsPocaIntel = new FuzzySet("PocoInteligente", new TrapezoidalFunction(0, 3, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsNeutraIntel = new FuzzySet("InteligenciaNeutra", new TrapezoidalFunction(4, 5, 6));
FuzzySet fsAltaIntel = new FuzzySet("MuyInteligente", new TrapezoidalFunction(7, 10, TrapezoidalFunction.EdgeType.Left));
LinguisticVariable lvInteligencia = new LinguisticVariable("Inteligencia", 0, 10);
lvInteligencia.AddLabel(fsPocaIntel);
lvInteligencia.AddLabel(fsNeutraIntel);
lvInteligencia.AddLabel(fsAltaIntel);
FuzzySet fsComplexionBaja = new FuzzySet("ComplexionBaja", new TrapezoidalFunction(0, 3, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsComplexionNeutra = new FuzzySet("ComplexionNeutra", new TrapezoidalFunction(4, 5, 6));
FuzzySet fsComplexionGrande = new FuzzySet("ComplexionGrande", new TrapezoidalFunction(7, 10, TrapezoidalFunction.EdgeType.Left));
LinguisticVariable lvComplexion = new LinguisticVariable("Complexion", 0, 10);
lvComplexion.AddLabel(fsComplexionBaja);
lvComplexion.AddLabel(fsComplexionNeutra);
lvComplexion.AddLabel(fsComplexionGrande);
FuzzySet fsTezClara = new FuzzySet("TezClara", new TrapezoidalFunction(0, 3, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsTezNeutra = new FuzzySet("TezNeutra", new TrapezoidalFunction(4, 5, 6));
FuzzySet fsTezOscura = new FuzzySet("TezOscura", new TrapezoidalFunction(7, 10, TrapezoidalFunction.EdgeType.Left));
LinguisticVariable lvTez = new LinguisticVariable("Tez", 0, 10);
lvTez.AddLabel(fsTezClara);
lvTez.AddLabel(fsTezNeutra);
lvTez.AddLabel(fsTezOscura);
FuzzySet fsBellezaBaja = new FuzzySet("No_Chido", new TrapezoidalFunction(0, 3, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsBellezaNeutra = new FuzzySet("Chido", new TrapezoidalFunction(4, 5, 6));
FuzzySet fsBellezaAlta = new FuzzySet("Muy_Chido", new TrapezoidalFunction(7, 10, TrapezoidalFunction.EdgeType.Left));
LinguisticVariable lvBelleza = new LinguisticVariable("Belleza", 0, 10);
lvBelleza.AddLabel(fsBellezaBaja);
lvBelleza.AddLabel(fsBellezaNeutra);
lvBelleza.AddLabel(fsBellezaAlta);
Console.WriteLine("INGRESA LA ESTATURA (140 a 190 cm)");
estatura = Convert.ToInt32(Console.ReadLine());
Console.WriteLine("INGRESA LA SIMPATIA (1=Mal Genio 10=Muy simpático)");
simpatia = Convert.ToInt32(Console.ReadLine());
Console.WriteLine("Ingresa la Inteligencia del 1 al 10 (No creo que deba explicarlo xd))");
inteligencia = Convert.ToInt32(Console.ReadLine());
Console.WriteLine("¿Qué complexión tiene? 1=Nada en forma 10=En forma B)");
complexion = Convert.ToInt32(Console.ReadLine());
Console.WriteLine("Ingresa la Tez 1=Oscura 10=Blanco");
tez = Convert.ToInt32(Console.ReadLine());
Database fuzzyDB = new Database();
fuzzyDB.AddVariable(lvEstatura);
fuzzyDB.AddVariable(lvSimpatia);
fuzzyDB.AddVariable(lvInteligencia);
fuzzyDB.AddVariable(lvComplexion);
fuzzyDB.AddVariable(lvTez);
fuzzyDB.AddVariable(lvBelleza);
IS = new InferenceSystem(fuzzyDB, new CentroidDefuzzifier(1000));
IS.NewRule("Rule 1", "IF Estatura IS Alto THEN Belleza IS Muy_Chido");
IS.NewRule("Rule 2", "IF Simpatia IS Agradable THEN Belleza IS Muy_Chido");
IS.NewRule("Rule 3", "IF Inteligencia IS MuyInteligente THEN Belleza IS Muy_Chido");
IS.NewRule("Rule 4", "IF Complexion IS ComplexionGrande THEN Belleza IS Muy_Chido");
IS.NewRule("Rule 5", "IF Tez IS TezOscura THEN Belleza IS Muy_Chido");
IS.NewRule("Rule 6", "IF Estatura IS Medio THEN Belleza IS Chido");
IS.NewRule("Rule 7", "IF Simpatia IS Neutro THEN Belleza IS Chido");
IS.NewRule("Rule 8", "IF Inteligencia IS InteligenciaNeutra THEN Belleza IS Chido");
IS.NewRule("Rule 9", "IF Complexion IS ComplexionNeutra THEN Belleza IS Chido");
IS.NewRule("Rule 10", "IF Tez IS TezNeutra THEN Belleza IS Chido");
IS.NewRule("Rule 11", "IF Estatura IS Bajo THEN Belleza IS No_Chido");
IS.NewRule("Rule 12", "IF Simpatia IS MalGenio THEN Belleza IS No_Chido");
IS.NewRule("Rule 13", "IF Inteligencia IS PocoInteligente THEN Belleza IS No_Chido");
IS.NewRule("Rule 14", "IF Complexion IS ComplexionBaja THEN Belleza IS No_Chido");
IS.NewRule("Rule 15", "IF Tez IS TezClara THEN Belleza IS No_Chido");
IS.SetInput("Estatura", estatura);
IS.SetInput("Simpatia", simpatia);
IS.SetInput("Inteligencia", inteligencia);
IS.SetInput("Complexion", complexion);
IS.SetInput("Tez", tez);
belleza = IS.Evaluate("Belleza");
//belleza.ToString("##0");
bellezaE = Convert.ToInt32(belleza.ToString("##0"));
Console.WriteLine("*****************************************************");
Console.WriteLine(belleza);
//Console.WriteLine(IS.SetInput("Belleza", belleza));
//Console.WriteLine(IS.GetLinguisticVariable("Belleza").GetLabel("Muy_Chido").Name);
switch (bellezaE)
{
case int n when(n >= 0 && n <= 3):
bellezaR = IS.GetLinguisticVariable("Belleza").GetLabel("No_Chido").Name.ToString();
break;
case int n when(n >= 4 && n <= 6):
bellezaR = IS.GetLinguisticVariable("Belleza").GetLabel("Chido").Name.ToString();
break;
case int n when(n >= 7 && n <= 10):
bellezaR = IS.GetLinguisticVariable("Belleza").GetLabel("Muy_Chido").Name.ToString();
break;
}
Console.WriteLine(bellezaR);
}
void InitFuzzyEngine()
{
// Linguistic labels (fuzzy sets) para aciertos
FuzzySet fsLow = new FuzzySet("Low", new TrapezoidalFunction(0.0, 0.33, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsNeutral = new FuzzySet("Normal", new TrapezoidalFunction(0.0, 0.33, 0.66, 1.00));
FuzzySet fsHigh = new FuzzySet("High", new TrapezoidalFunction(0.66, 1.00, TrapezoidalFunction.EdgeType.Left));
/* // Linguistic labels (fuzzy sets) para errores y ayuda
* FuzzySet fsLowInv = new FuzzySet("Low", new TrapezoidalFunction(0.0, 0.33, TrapezoidalFunction.EdgeType.Right));
* FuzzySet fsHighInv = new FuzzySet("High", new TrapezoidalFunction(0.66, 1.00, TrapezoidalFunction.EdgeType.Left));
*/
// Linguistic labels (fuzzy sets) para el tiempo
FuzzySet fsFast = new FuzzySet("Fast", new TrapezoidalFunction(0, 0.33, TrapezoidalFunction.EdgeType.Left));
FuzzySet fsNormal = new FuzzySet("Normal", new TrapezoidalFunction(0, 0.33, 0.66, 1.00));
FuzzySet fsSlow = new FuzzySet("Slow", new TrapezoidalFunction(0.66, 1.00, TrapezoidalFunction.EdgeType.Right));
// Right Distance (Input)
LinguisticVariable numAciertos = new LinguisticVariable("Aciertos", 0, 1);
numAciertos.AddLabel(fsLow);
numAciertos.AddLabel(fsNeutral);
numAciertos.AddLabel(fsHigh);
// Left Distance (Input)
LinguisticVariable numErrores = new LinguisticVariable("Errores", 0, 1);
numErrores.AddLabel(fsLow);
numErrores.AddLabel(fsNeutral);
numErrores.AddLabel(fsHigh);
LinguisticVariable ayudas = new LinguisticVariable("Ayuda", 0, 1);
ayudas.AddLabel(fsLow);
ayudas.AddLabel(fsNeutral);
ayudas.AddLabel(fsHigh);
// Time (Input)
LinguisticVariable tiempoSeg = new LinguisticVariable("Time", 0, 1);
tiempoSeg.AddLabel(fsSlow);
tiempoSeg.AddLabel(fsNormal);
tiempoSeg.AddLabel(fsFast);
// Linguistic labels (fuzzy sets) that compose Dificultad
FuzzySet fsVeryWeak = new FuzzySet("VeryWeak", new TrapezoidalFunction(0.0, 0.20, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsWeak = new FuzzySet("Weak", new TrapezoidalFunction(0.0, 0.20, 0.35, 0.40));
FuzzySet fsBasico = new FuzzySet("Normal", new TrapezoidalFunction(0.35, 0.40, 0.55, 0.60));
FuzzySet fsGood = new FuzzySet("Good", new TrapezoidalFunction(0.55, 0.60, 0.75, 0.80));
FuzzySet fsGreat = new FuzzySet("Great", new TrapezoidalFunction(0.75, 0.80, TrapezoidalFunction.EdgeType.Left));
// AnglefsWonderFull
lvDificultad = new LinguisticVariable("Dificultad", 0, 1.00);
lvDificultad.AddLabel(fsVeryWeak);
lvDificultad.AddLabel(fsWeak);
lvDificultad.AddLabel(fsBasico);
lvDificultad.AddLabel(fsGood);
lvDificultad.AddLabel(fsGreat);
// The database
Database fuzzyDB = new Database();
fuzzyDB.AddVariable(numAciertos);
fuzzyDB.AddVariable(numErrores);
fuzzyDB.AddVariable(tiempoSeg);
fuzzyDB.AddVariable(ayudas);
fuzzyDB.AddVariable(lvDificultad);
// Creating the inference system
IS = new InferenceSystem(fuzzyDB, new CentroidDefuzzifier(1500));
IS.NewRule("RULE 1", "IF Time IS Fast AND Ayuda IS Low AND Errores IS Low AND Aciertos IS Low THEN Dificultad IS Weak");
IS.NewRule("RULE 2", "IF Time IS Fast AND Ayuda IS Low AND Errores IS Low AND Aciertos IS Normal THEN Dificultad IS Good");
IS.NewRule("RULE 3", "IF Time IS Fast AND Ayuda IS Low AND Errores IS Low AND Aciertos IS High THEN Dificultad IS Great");
IS.NewRule("RULE 4", "IF Time IS Fast AND Ayuda IS Low AND Errores IS Normal AND Aciertos IS Low THEN Dificultad IS Normal");
IS.NewRule("RULE 5", "IF Time IS Fast AND Ayuda IS Low AND Errores IS Normal AND Aciertos IS Normal THEN Dificultad IS Normal");
IS.NewRule("RULE 6", "IF Time IS Fast AND Ayuda IS Low AND Errores IS Normal AND Aciertos IS High THEN Dificultad IS Good");
IS.NewRule("RULE 7", "IF Time IS Fast AND Ayuda IS Low AND Errores IS High AND Aciertos IS Low THEN Dificultad IS Weak");
IS.NewRule("RULE 8", "IF Time IS Fast AND Ayuda IS Low AND Errores IS High AND Aciertos IS Normal THEN Dificultad IS Normal");
IS.NewRule("RULE 9", "IF Time IS Fast AND Ayuda IS Low AND Errores IS High AND Aciertos IS High THEN Dificultad IS Normal");
IS.NewRule("RULE 10", "IF Time IS Fast AND Ayuda IS Normal AND Errores IS Low AND Aciertos IS Low THEN Dificultad IS Weak");
IS.NewRule("RULE 11", "IF Time IS Fast AND Ayuda IS Normal AND Errores IS Low AND Aciertos IS Normal THEN Dificultad IS Normal");
IS.NewRule("RULE 12", "IF Time IS Fast AND Ayuda IS Normal AND Errores IS Low AND Aciertos IS High THEN Dificultad IS Great");
IS.NewRule("RULE 13", "IF Time IS Fast AND Ayuda IS Normal AND Errores IS Normal AND Aciertos IS Low THEN Dificultad IS Weak");
IS.NewRule("RULE 14", "IF Time IS Fast AND Ayuda IS Normal AND Errores IS Normal AND Aciertos IS Normal THEN Dificultad IS Good");
IS.NewRule("RULE 15", "IF Time IS Fast AND Ayuda IS Normal AND Errores IS Normal AND Aciertos IS High THEN Dificultad IS Good");
IS.NewRule("RULE 16", "IF Time IS Fast AND Ayuda IS Normal AND Errores IS High AND Aciertos IS Low THEN Dificultad IS Weak");
IS.NewRule("RULE 17", "IF Time IS Fast AND Ayuda IS Normal AND Errores IS High AND Aciertos IS Normal THEN Dificultad IS Weak");
IS.NewRule("RULE 18", "IF Time IS Fast AND Ayuda IS Normal AND Errores IS High AND Aciertos IS High THEN Dificultad IS Normal");
IS.NewRule("RULE 19", "IF Time IS Fast AND Ayuda IS High AND Errores IS Low AND Aciertos IS Low THEN Dificultad IS Weak");
IS.NewRule("RULE 20", "IF Time IS Fast AND Ayuda IS High AND Errores IS Low AND Aciertos IS Normal THEN Dificultad IS Normal");
IS.NewRule("RULE 21", "IF Time IS Fast AND Ayuda IS High AND Errores IS Low AND Aciertos IS High THEN Dificultad IS Good");
IS.NewRule("RULE 22", "IF Time IS Fast AND Ayuda IS High AND Errores IS Normal AND Aciertos IS Low THEN Dificultad IS Weak");
IS.NewRule("RULE 23", "IF Time IS Fast AND Ayuda IS High AND Errores IS Normal AND Aciertos IS Normal THEN Dificultad IS Normal");
IS.NewRule("RULE 24", "IF Time IS Fast AND Ayuda IS High AND Errores IS Normal AND Aciertos IS High THEN Dificultad IS Normal");
IS.NewRule("RULE 25", "IF Time IS Fast AND Ayuda IS High AND Errores IS High AND Aciertos IS Low THEN Dificultad IS Weak");
IS.NewRule("RULE 26", "IF Time IS Fast AND Ayuda IS High AND Errores IS High AND Aciertos IS Normal THEN Dificultad IS Weak");
IS.NewRule("RULE 27", "IF Time IS Fast AND Ayuda IS High AND Errores IS High AND Aciertos IS High THEN Dificultad IS Normal");
IS.NewRule("RULE 28", "IF Time IS Normal AND Ayuda IS Low AND Errores IS Low AND Aciertos IS Low THEN Dificultad IS Weak");
IS.NewRule("RULE 29", "IF Time IS Normal AND Ayuda IS Low AND Errores IS Low AND Aciertos IS Normal THEN Dificultad IS Normal");
IS.NewRule("RULE 30", "IF Time IS Normal AND Ayuda IS Low AND Errores IS Low AND Aciertos IS High THEN Dificultad IS Great");
IS.NewRule("RULE 31", "IF Time IS Normal AND Ayuda IS Low AND Errores IS Normal AND Aciertos IS Low THEN Dificultad IS Normal");
IS.NewRule("RULE 32", "IF Time IS Normal AND Ayuda IS Low AND Errores IS Normal AND Aciertos IS Normal THEN Dificultad IS Normal");
IS.NewRule("RULE 33", "IF Time IS Normal AND Ayuda IS Low AND Errores IS Normal AND Aciertos IS High THEN Dificultad IS Good");
IS.NewRule("RULE 34", "IF Time IS Normal AND Ayuda IS Low AND Errores IS High AND Aciertos IS Low THEN Dificultad IS Weak");
IS.NewRule("RULE 35", "IF Time IS Normal AND Ayuda IS Low AND Errores IS High AND Aciertos IS Normal THEN Dificultad IS Normal");
IS.NewRule("RULE 36", "IF Time IS Normal AND Ayuda IS Low AND Errores IS High AND Aciertos IS High THEN Dificultad IS Normal");
IS.NewRule("RULE 37", "IF Time IS Normal AND Ayuda IS Normal AND Errores IS Low AND Aciertos IS Low THEN Dificultad IS Normal");
IS.NewRule("RULE 38", "IF Time IS Normal AND Ayuda IS Normal AND Errores IS Low AND Aciertos IS Normal THEN Dificultad IS Normal");
IS.NewRule("RULE 39", "IF Time IS Normal AND Ayuda IS Normal AND Errores IS Low AND Aciertos IS High THEN Dificultad IS Good");
IS.NewRule("RULE 40", "IF Time IS Normal AND Ayuda IS Normal AND Errores IS Normal AND Aciertos IS Low THEN Dificultad IS Normal");
IS.NewRule("RULE 41", "IF Time IS Normal AND Ayuda IS Normal AND Errores IS Normal AND Aciertos IS Normal THEN Dificultad IS Normal");
IS.NewRule("RULE 42", "IF Time IS Normal AND Ayuda IS Normal AND Errores IS Normal AND Aciertos IS High THEN Dificultad IS Good");
IS.NewRule("RULE 43", "IF Time IS Normal AND Ayuda IS Normal AND Errores IS High AND Aciertos IS Low THEN Dificultad IS Weak");
IS.NewRule("RULE 44", "IF Time IS Normal AND Ayuda IS Normal AND Errores IS High AND Aciertos IS Normal THEN Dificultad IS Weak");
IS.NewRule("RULE 45", "IF Time IS Normal AND Ayuda IS Normal AND Errores IS High AND Aciertos IS High THEN Dificultad IS Normal");
IS.NewRule("RULE 46", "IF Time IS Normal AND Ayuda IS High AND Errores IS Low AND Aciertos IS Low THEN Dificultad IS Weak");
IS.NewRule("RULE 47", "IF Time IS Normal AND Ayuda IS High AND Errores IS Low AND Aciertos IS Normal THEN Dificultad IS Normal");
IS.NewRule("RULE 48", "IF Time IS Normal AND Ayuda IS High AND Errores IS Low AND Aciertos IS High THEN Dificultad IS Good");
IS.NewRule("RULE 49", "IF Time IS Normal AND Ayuda IS High AND Errores IS Normal AND Aciertos IS Low THEN Dificultad IS Weak");
IS.NewRule("RULE 50", "IF Time IS Normal AND Ayuda IS High AND Errores IS Normal AND Aciertos IS Normal THEN Dificultad IS Normal");
IS.NewRule("RULE 51", "IF Time IS Normal AND Ayuda IS High AND Errores IS Normal AND Aciertos IS High THEN Dificultad IS Normal");
IS.NewRule("RULE 52", "IF Time IS Normal AND Ayuda IS High AND Errores IS High AND Aciertos IS Low THEN Dificultad IS VeryWeak");
IS.NewRule("RULE 53", "IF Time IS Normal AND Ayuda IS High AND Errores IS High AND Aciertos IS Normal THEN Dificultad IS Weak");
IS.NewRule("RULE 54", "IF Time IS Normal AND Ayuda IS High AND Errores IS High AND Aciertos IS High THEN Dificultad IS Normal");
IS.NewRule("RULE 55", "IF Time IS Slow AND Ayuda IS Low AND Errores IS Low AND Aciertos IS Low THEN Dificultad IS Normal");
IS.NewRule("RULE 56", "IF Time IS Slow AND Ayuda IS Low AND Errores IS Low AND Aciertos IS Normal THEN Dificultad IS Normal");
IS.NewRule("RULE 57", "IF Time IS Slow AND Ayuda IS Low AND Errores IS Low AND Aciertos IS High THEN Dificultad IS Good");
IS.NewRule("RULE 58", "IF Time IS Slow AND Ayuda IS Low AND Errores IS Normal AND Aciertos IS Low THEN Dificultad IS Weak");
IS.NewRule("RULE 59", "IF Time IS Slow AND Ayuda IS Low AND Errores IS Normal AND Aciertos IS Normal THEN Dificultad IS Normal");
IS.NewRule("RULE 60", "IF Time IS Slow AND Ayuda IS Low AND Errores IS Normal AND Aciertos IS High THEN Dificultad IS Good");
IS.NewRule("RULE 61", "IF Time IS Slow AND Ayuda IS Low AND Errores IS High AND Aciertos IS Low THEN Dificultad IS Weak");
IS.NewRule("RULE 62", "IF Time IS Slow AND Ayuda IS Low AND Errores IS High AND Aciertos IS Normal THEN Dificultad IS Normal");
IS.NewRule("RULE 63", "IF Time IS Slow AND Ayuda IS Low AND Errores IS High AND Aciertos IS High THEN Dificultad IS Normal");
IS.NewRule("RULE 64", "IF Time IS Slow AND Ayuda IS Normal AND Errores IS Low AND Aciertos IS Low THEN Dificultad IS VeryWeak");
IS.NewRule("RULE 65", "IF Time IS Slow AND Ayuda IS Normal AND Errores IS Low AND Aciertos IS Normal THEN Dificultad IS Normal");
IS.NewRule("RULE 66", "IF Time IS Slow AND Ayuda IS Normal AND Errores IS Low AND Aciertos IS High THEN Dificultad IS Good");
IS.NewRule("RULE 67", "IF Time IS Slow AND Ayuda IS Normal AND Errores IS Normal AND Aciertos IS Low THEN Dificultad IS Weak");
IS.NewRule("RULE 68", "IF Time IS Slow AND Ayuda IS Normal AND Errores IS Normal AND Aciertos IS Normal THEN Dificultad IS Normal");
IS.NewRule("RULE 69", "IF Time IS Slow AND Ayuda IS Normal AND Errores IS Normal AND Aciertos IS High THEN Dificultad IS Normal");
IS.NewRule("RULE 70", "IF Time IS Slow AND Ayuda IS Normal AND Errores IS High AND Aciertos IS Low THEN Dificultad IS VeryWeak");
IS.NewRule("RULE 71", "IF Time IS Slow AND Ayuda IS Normal AND Errores IS High AND Aciertos IS Normal THEN Dificultad IS Weak");
IS.NewRule("RULE 72", "IF Time IS Slow AND Ayuda IS Normal AND Errores IS High AND Aciertos IS High THEN Dificultad IS Normal");
IS.NewRule("RULE 73", "IF Time IS Slow AND Ayuda IS High AND Errores IS Low AND Aciertos IS Low THEN Dificultad IS Weak");
IS.NewRule("RULE 74", "IF Time IS Slow AND Ayuda IS High AND Errores IS Low AND Aciertos IS Normal THEN Dificultad IS Weak");
IS.NewRule("RULE 75", "IF Time IS Slow AND Ayuda IS High AND Errores IS Low AND Aciertos IS High THEN Dificultad IS Normal");
IS.NewRule("RULE 76", "IF Time IS Slow AND Ayuda IS High AND Errores IS Normal AND Aciertos IS Low THEN Dificultad IS VeryWeak");
IS.NewRule("RULE 77", "IF Time IS Slow AND Ayuda IS High AND Errores IS Normal AND Aciertos IS Normal THEN Dificultad IS Weak");
IS.NewRule("RULE 78", "IF Time IS Slow AND Ayuda IS High AND Errores IS Normal AND Aciertos IS High THEN Dificultad IS Normal");
IS.NewRule("RULE 79", "IF Time IS Slow AND Ayuda IS High AND Errores IS High AND Aciertos IS Low THEN Dificultad IS VeryWeak");
IS.NewRule("RULE 80", "IF Time IS Slow AND Ayuda IS High AND Errores IS High AND Aciertos IS Normal THEN Dificultad IS VeryWeak");
IS.NewRule("RULE 81", "IF Time IS Slow AND Ayuda IS High AND Errores IS High AND Aciertos IS High THEN Dificultad IS Weak");
}
/// <summary>
/// Define regras fuzzy
/// </summary>
private void SetRules()
{
// Regras da Reta
IS.NewRule("R1", "IF RoadSegment IS Reta And Frontal IS FarF AND Left IS FarS THEN Angle IS VeryLittleNegative");
IS.NewRule("R2", "IF RoadSegment IS Reta And Frontal IS FarF AND Right IS FarS THEN Angle IS VeryLittlePositive");
IS.NewRule("R3", "IF RoadSegment IS Reta And Frontal IS FarF THEN Angle IS Zero");
IS.NewRule("R4", "IF RoadSegment IS Reta And Frontal IS MediumF AND Left Is FarS THEN Angle IS VeryLittleNegative");
IS.NewRule("R5", "IF RoadSegment IS Reta And Frontal IS MediumF AND Right Is FarS THEN Angle IS VeryLittlePositive");
IS.NewRule("R6", "IF RoadSegment IS Reta And Right Is NearS THEN Angle IS VeryLittleNegative");
IS.NewRule("R7", "IF RoadSegment IS Reta And Frontal Is NearF AND Right IS FarS THEN Angle IS Positive");
IS.NewRule("R8", "IF RoadSegment IS Reta And Frontal Is VeryNearF AND Right IS FarS THEN Angle IS Positive");
// Regras da Curva
IS.NewRule("R9", "IF RoadSegment IS Curva And CurvedFrontalLeft Is FarCF Then Angle IS VeryNegative");
IS.NewRule("R10", "IF RoadSegment IS Curva And CurvedFrontalRight Is FarCF THEN Angle IS VeryPositive");
IS.NewRule("R11", "IF RoadSegment IS Curva And RightFront Is FarS THEN Angle IS Positive");
IS.NewRule("R12", "IF RoadSegment IS Curva And Right Is FarS THEN Angle IS Positive");
IS.NewRule("R13", "IF RoadSegment IS Curva And RightRear Is FarS THEN Angle IS Positive");
IS.NewRule("R14", "IF RoadSegment IS Curva And Frontal Is FarF THEN Angle IS Zero");
IS.NewRule("R15", "IF RoadSegment IS Curva And FrontalRight Is FarF THEN Angle IS Zero");
IS.NewRule("R16", "IF RoadSegment IS Curva And FrontalLeft Is FarF THEN Angle IS Zero");
IS.NewRule("R17", "IF RoadSegment IS Curva And LeftFront Is FarS THEN Angle IS Negative");
IS.NewRule("R18", "IF RoadSegment IS Curva And Left Is FarS THEN Angle IS Negative");
IS.NewRule("R19", "IF RoadSegment IS Curva And LeftRear Is FarS THEN Angle IS Negative");
IS.NewRule("R20", "IF RoadSegment IS Curva And CurvedFrontalLeft Is NearCF Then Angle IS VeryPositive");
IS.NewRule("R21", "IF RoadSegment IS Curva And LeftFront Is FarS THEN Angle IS Negative");
IS.NewRule("R22", "IF RoadSegment IS Curva And RightFront Is FarS THEN Angle IS Positive");
IS.NewRule("R23", "IF RoadSegment IS Curva And LeftFront Is FarS AND Left IS FarS AND LeftRear IS FarS THEN Angle IS VeryNegative");
IS.NewRule("R24", "IF RoadSegment IS Curva And RightFront Is FarS AND Right IS FarS AND RightRear IS FarS THEN Angle IS VeryPositive");
IS.NewRule("R25", "IF RoadSegment IS Curva And CurvedFrontalRight Is NearCF Then Angle IS VeryNegative");
//Regras RF
IS.NewRule("R26", "IF RoadSegment IS Reta And RightFront IS FarS THEN Angle IS VeryLittlePositive");
IS.NewRule("R27", "IF RoadSegment IS Reta And RightFront Is FarS THEN Angle IS VeryLittlePositive");
IS.NewRule("R28", "IF RoadSegment IS Reta And RightFront Is MediumS THEN Angle IS Zero");
//Regras RR
IS.NewRule("R29", "IF RoadSegment IS Reta And RightRear IS FarS THEN Angle IS VeryLittlePositive");
IS.NewRule("R30", "IF RoadSegment IS Reta And RightRear Is FarS THEN Angle IS VeryLittlePositive");
IS.NewRule("R31", "IF RoadSegment IS Reta And RightRear Is MediumS THEN Angle IS Zero");
//Regras LF
IS.NewRule("R32", "IF RoadSegment IS Reta And LeftFront IS FarS THEN Angle IS VeryLittleNegative");
IS.NewRule("R33", "IF RoadSegment IS Reta And LeftFront Is FarS THEN Angle IS VeryLittleNegative");
IS.NewRule("R34", "IF RoadSegment IS Reta And LeftFront Is MediumS THEN Angle IS Zero");
//Regras LR
IS.NewRule("R35", "IF RoadSegment IS Reta And LeftRear IS FarS THEN Angle IS VeryLittleNegative");
IS.NewRule("R36", "IF RoadSegment IS Reta And LeftRear Is FarS THEN Angle IS VeryLittleNegative");
IS.NewRule("R37", "IF RoadSegment IS Reta And LeftRear Is MediumS THEN Angle IS Zero");
// Regras Sensores Frontais
IS.NewRule("R38", "IF RoadSegment IS Reta And FrontalRight Is NearF AND Right IS FarS THEN Angle IS Positive");
IS.NewRule("R39", "IF RoadSegment IS Reta And FrontalRight Is VeryNearF AND Right IS FarS THEN Angle IS Positive");
IS.NewRule("R40", "IF RoadSegment IS Reta And FrontalLeft Is NearF AND Right IS FarS THEN Angle IS Positive");
IS.NewRule("R41", "IF RoadSegment IS Reta And FrontalLeft Is VeryNearF AND Right IS FarS THEN Angle IS Positive");
IS.NewRule("R42", "IF RoadSegment IS Reta And CurvedFrontalLeft Is FarCF Then Angle IS Negative");
IS.NewRule("R43", "IF RoadSegment IS Reta And CurvedFrontalRight Is FarCF THEN Angle IS Positive");
// Aceleração
IS.NewRule("R44", "IF RoadSegment IS Reta AND Frontal IS FarF AND FrontalRight IS FarF AND FrontalLeft IS FarF THEN Acceleration IS VeryFast");
IS.NewRule("R45", "IF RoadSegment IS Reta AND Frontal IS MediumF AND FrontalRight IS MediumF AND FrontalLeft IS MediumF THEN Acceleration IS Fast");
IS.NewRule("R46", "IF RoadSegment IS Reta AND CurvedFrontalRight IS NearCF THEN Acceleration IS Slow");
IS.NewRule("R47", "IF RoadSegment IS Reta AND CurvedFrontalRight IS VeryNearCF THEN Acceleration IS Slow");
IS.NewRule("R48", "IF RoadSegment IS Reta AND Frontal IS NearF AND FrontalRight IS NearF AND FrontalLeft IS NearF THEN Acceleration IS Stop");
IS.NewRule("R49", "IF RoadSegment IS Reta AND Frontal IS NearF AND FrontalRight IS NearF AND FrontalLeft IS NearF THEN Acceleration IS Stop");
IS.NewRule("R50", "IF CurvedFrontalLeft IS VeryNearCF THEN Acceleration IS Stop");
IS.NewRule("R51", "IF CurvedFrontalRight IS VeryNearCF THEN Acceleration IS Stop");
IS.NewRule("R52", "IF RoadSegment IS Reta AND Frontal IS FarF AND FrontalRight IS FarF AND FrontalLeft IS NOT FarF THEN Acceleration IS Normal");
IS.NewRule("R53", "IF RoadSegment IS Reta AND Frontal IS FarF AND FrontalLeft IS FarF AND FrontalRight IS NOT FarF THEN Acceleration IS Normal");
IS.NewRule("R54", "IF RoadSegment IS Curva AND Frontal IS NearF THEN Acceleration IS Slow");
IS.NewRule("R55", "IF RoadSegment IS Curva AND Frontal IS MediumF THEN Acceleration IS Normal");
IS.NewRule("R56", "IF RoadSegment IS Curva AND Frontal IS FarF THEN Acceleration IS Normal");
IS.NewRule("R57", "IF RoadSegment IS Curva AND Frontal IS FarF AND FrontalRight IS FarF AND FrontalLeft IS FarF THEN Acceleration IS VeryFast");
IS.NewRule("R58", "IF RoadSegment IS Curva THEN Acceleration IS Slow");
IS.NewRule("R59", "IF RoadSegment IS Curva AND Frontal IS MediumF AND FrontalRight IS MediumF AND FrontalLeft IS MediumF THEN Acceleration IS Fast");
IS.NewRule("R60", "IF RoadSegment IS Reta AND CurvedFrontalRight IS NOT NearCF AND CurvedFrontalRight IS NOT VeryNearCF AND CurvedFrontalLeft IS NOT NearCF AND CurvedFrontalLeft IS NOT VeryNearCF THEN Acceleration IS Fast");
IS.NewRule("R61", "IF CurvedFrontalLeft IS VeryNearCF THEN Angle IS Positive");
IS.NewRule("R62", "IF CurvedFrontalRight IS VeryNearCF THEN Angle IS Negative");
// Carro adversario
IS.NewRule("R63", "IF RoadSegment IS Reta And CarroAdversario IS Right THEN Angle IS Positive");
IS.NewRule("R64", "IF RoadSegment IS Reta And CarroAdversario IS RightFront THEN Angle IS Positive");
IS.NewRule("R65", "IF RoadSegment IS Reta And CarroAdversario IS RightRear THEN Angle IS Positive");
IS.NewRule("R66", "IF RoadSegment IS Curva And CarroAdversario IS Right THEN Angle IS VeryPositive");
IS.NewRule("R67", "IF RoadSegment IS Curva And CarroAdversario IS RightFront THEN Angle IS VeryPositive");
IS.NewRule("R68", "IF RoadSegment IS Curva And CarroAdversario IS RightRear THEN Angle IS VeryPositive");
}
private void bunifuImageButton9_Click(object sender, EventArgs e)
{
// Kecepatan (0-120)
FuzzySet fsLambat = new FuzzySet("Lambat", new TrapezoidalFunction(30, 50, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsSedang = new FuzzySet("Sedang", new TrapezoidalFunction(40, 60, 80));
FuzzySet fsCepat = new FuzzySet("Cepat", new TrapezoidalFunction(70, 80, TrapezoidalFunction.EdgeType.Left));
// Linguistik Kecepatan
LinguisticVariable lvKecepatan = new LinguisticVariable("Kecepatan", 0, 120);
lvKecepatan.AddLabel(fsLambat);
lvKecepatan.AddLabel(fsSedang);
lvKecepatan.AddLabel(fsCepat);
// Jarak (0-10)
FuzzySet fsDekat = new FuzzySet("Dekat", new TrapezoidalFunction(1, 2, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsJauh = new FuzzySet("Jauh", new TrapezoidalFunction(1, 4, 5));
FuzzySet fsSangatJauh = new FuzzySet("SangatJauh", new TrapezoidalFunction(4, 7, TrapezoidalFunction.EdgeType.Left));
// Linguistik Jarak
LinguisticVariable lvJarak = new LinguisticVariable("Jarak", 0, 10);
lvJarak.AddLabel(fsDekat);
lvJarak.AddLabel(fsJauh);
lvJarak.AddLabel(fsSangatJauh);
// Kemiringan Jalan ((-90)-90)
FuzzySet fsTurun = new FuzzySet("Turun", new TrapezoidalFunction(-40, -20, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsDatar = new FuzzySet("Datar", new TrapezoidalFunction(-25, 0, 25));
FuzzySet fsNaik = new FuzzySet("Naik", new TrapezoidalFunction(20, 40, TrapezoidalFunction.EdgeType.Left));
// Linguistik Kemiringan Jalan
LinguisticVariable lvKemiringan = new LinguisticVariable("Kemiringan", -90, 90);
lvKemiringan.AddLabel(fsTurun);
lvKemiringan.AddLabel(fsDatar);
lvKemiringan.AddLabel(fsNaik);
// OUTPUT
// Tingkat Pengereman (0-10)
FuzzySet fsLemah = new FuzzySet("Lemah", new TrapezoidalFunction(3, 4, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsMedium = new FuzzySet("Sedang", new TrapezoidalFunction(3, 4, 6, 7));
FuzzySet fsKuat = new FuzzySet("Kuat", new TrapezoidalFunction(6, 7, TrapezoidalFunction.EdgeType.Left));
// Linguistik Kecepatan
LinguisticVariable lvTingkatPengereman = new LinguisticVariable("TingkatPengereman", 0, 10);
lvTingkatPengereman.AddLabel(fsLemah);
lvTingkatPengereman.AddLabel(fsMedium);
lvTingkatPengereman.AddLabel(fsKuat);
// Database
Database fuzzyDB = new Database();
fuzzyDB.AddVariable(lvJarak);
fuzzyDB.AddVariable(lvKemiringan);
fuzzyDB.AddVariable(lvKecepatan);
fuzzyDB.AddVariable(lvTingkatPengereman);
// Inferensi System Engine
InferenceSystem IS = new InferenceSystem(fuzzyDB, new CentroidDefuzzifier(1000));
// Rules
IS.NewRule("Rule 1", "IF Kecepatan IS Lambat AND Jarak IS Dekat AND Kemiringan IS Turun THEN TingkatPengereman IS Kuat");
IS.NewRule("Rule 2", "IF Kecepatan IS Lambat AND Jarak IS Dekat AND Kemiringan IS Naik THEN TingkatPengereman IS Lemah");
IS.NewRule("Rule 3", "IF Kecepatan IS Lambat AND Jarak IS Dekat AND Kemiringan IS Datar THEN TingkatPengereman IS Sedang");
IS.NewRule("Rule 4", "IF Kecepatan IS Lambat AND Jarak IS Jauh AND Kemiringan IS Datar THEN TingkatPengereman IS Lemah");
IS.NewRule("Rule 5", "IF Kecepatan IS Lambat AND Jarak IS Jauh AND Kemiringan IS Naik THEN TingkatPengereman IS Lemah");
IS.NewRule("Rule 6", "IF Kecepatan IS Lambat AND Jarak IS Jauh AND Kemiringan IS Turun THEN TingkatPengereman IS Sedang");
IS.NewRule("Rule 7", "IF Kecepatan IS Lambat AND Jarak IS SangatJauh AND Kemiringan IS Datar THEN TingkatPengereman IS Lemah");
IS.NewRule("Rule 8", "IF Kecepatan IS Lambat AND Jarak IS SangatJauh AND Kemiringan IS Naik THEN TingkatPengereman IS Lemah");
IS.NewRule("Rule 9", "IF Kecepatan IS Lambat AND Jarak IS SangatJauh AND Kemiringan IS Turun THEN TingkatPengereman IS Sedang");
IS.NewRule("Rule 10", "IF Kecepatan IS Sedang AND Jarak IS Dekat AND Kemiringan IS Datar THEN TingkatPengereman IS Kuat");
IS.NewRule("Rule 11", "IF Kecepatan IS Sedang AND Jarak IS Dekat AND Kemiringan IS Naik THEN TingkatPengereman IS Sedang");
IS.NewRule("Rule 12", "IF Kecepatan IS Sedang AND Jarak IS Dekat AND Kemiringan IS Turun THEN TingkatPengereman IS Kuat");
IS.NewRule("Rule 13", "IF Kecepatan IS Sedang AND Jarak IS Jauh AND Kemiringan IS Datar THEN TingkatPengereman IS Sedang");
IS.NewRule("Rule 14", "IF Kecepatan IS Sedang AND Jarak IS Jauh AND Kemiringan IS Naik THEN TingkatPengereman IS Lemah");
IS.NewRule("Rule 15", "IF Kecepatan IS Sedang AND Jarak IS Jauh AND Kemiringan IS Turun THEN TingkatPengereman IS Kuat");
IS.NewRule("Rule 16", "IF Kecepatan IS Sedang AND Jarak IS SangatJauh AND Kemiringan IS Datar THEN TingkatPengereman IS Lemah");
IS.NewRule("Rule 17", "IF Kecepatan IS Sedang AND Jarak IS SangatJauh AND Kemiringan IS Naik THEN TingkatPengereman IS Lemah");
IS.NewRule("Rule 18", "IF Kecepatan IS Sedang AND Jarak IS SangatJauh AND Kemiringan IS Turun THEN TingkatPengereman IS Sedang");
IS.NewRule("Rule 19", "IF Kecepatan IS Cepat AND Jarak IS Dekat AND Kemiringan IS Datar THEN TingkatPengereman IS Kuat");
IS.NewRule("Rule 20", "IF Kecepatan IS Cepat AND Jarak IS Dekat AND Kemiringan IS Naik THEN TingkatPengereman IS Sedang");
IS.NewRule("Rule 21", "IF Kecepatan IS Cepat AND Jarak IS Dekat AND Kemiringan IS Turun THEN TingkatPengereman IS Kuat");
IS.NewRule("Rule 22", "IF Kecepatan IS Cepat AND Jarak IS Jauh AND Kemiringan IS Datar THEN TingkatPengereman IS Kuat");
IS.NewRule("Rule 23", "IF Kecepatan IS Cepat AND Jarak IS Jauh AND Kemiringan IS Naik THEN TingkatPengereman IS Sedang");
IS.NewRule("Rule 24", "IF Kecepatan IS Cepat AND Jarak IS Jauh AND Kemiringan IS Turun THEN TingkatPengereman IS Kuat");
IS.NewRule("Rule 25", "IF Kecepatan IS Cepat AND Jarak IS SangatJauh AND Kemiringan IS Datar THEN TingkatPengereman IS Sedang");
IS.NewRule("Rule 26", "IF Kecepatan IS Cepat AND Jarak IS SangatJauh AND Kemiringan IS Naik THEN TingkatPengereman IS Lemah");
IS.NewRule("Rule 27", "IF Kecepatan IS Cepat AND Jarak IS SangatJauh AND Kemiringan IS Turun THEN TingkatPengereman IS Kuat");
// Set Input
IS.SetInput("Kecepatan", (float)Convert.ToDouble(TB_Speed.Value));
IS.SetInput("Jarak", (float)Convert.ToDouble(TB_Distance.Value));
if (TB_AngleMin.Value != 0)
{
IS.SetInput("Kemiringan", (float)Convert.ToDouble(TB_AngleMin.Value));
}
IS.SetInput("Kemiringan", (float)Convert.ToDouble(TB_AnglePlus.Value));
// Get output
double BrakeLevel = IS.Evaluate("TingkatPengereman");
if (TB_Speed.Value == 0 && TB_Distance.Value == 0 && TB_AngleMin.Value == 0 && TB_AnglePlus.Value == 0)
{
BrakeLevel = 0;
Gauge_Break.Value = Convert.ToInt32(BrakeLevel * 10);
lblvalueBrake.Text = Convert.ToString(Math.Ceiling(BrakeLevel));
}
else
{
Gauge_Break.Value = Convert.ToInt32(BrakeLevel * 10);
}
lblvalueBrake.Text = Convert.ToString(Math.Ceiling(BrakeLevel));
}
public void JNCK()
{
InitializeComponent();
// INPUT
// Kecepatan (0-120)
FuzzySet fsLambat = new FuzzySet("Lambat", new TrapezoidalFunction(30, 50, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsSedang = new FuzzySet("Sedang", new TrapezoidalFunction(40, 60, 80));
FuzzySet fsCepat = new FuzzySet("Cepat", new TrapezoidalFunction(70, 80, TrapezoidalFunction.EdgeType.Left));
// Linguistik Kecepatan
LinguisticVariable lvKecepatan = new LinguisticVariable("Kecepatan", 0, 120);
lvKecepatan.AddLabel(fsLambat);
lvKecepatan.AddLabel(fsSedang);
lvKecepatan.AddLabel(fsCepat);
// Jarak (0-10)
FuzzySet fsDekat = new FuzzySet("Dekat", new TrapezoidalFunction(1, 2, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsJauh = new FuzzySet("Jauh", new TrapezoidalFunction(1, 4, 5));
FuzzySet fsSangatJauh = new FuzzySet("SangatJauh", new TrapezoidalFunction(4, 7, TrapezoidalFunction.EdgeType.Left));
// Linguistik Jarak
LinguisticVariable lvJarak = new LinguisticVariable("Jarak", 0, 10);
lvJarak.AddLabel(fsDekat);
lvJarak.AddLabel(fsJauh);
lvJarak.AddLabel(fsSangatJauh);
// Kemiringan Jalan ((-90)-90)
FuzzySet fsTurun = new FuzzySet("Turun", new TrapezoidalFunction(-40, -20, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsDatar = new FuzzySet("Datar", new TrapezoidalFunction(-25, 0, 25));
FuzzySet fsNaik = new FuzzySet("Naik", new TrapezoidalFunction(20, 40, TrapezoidalFunction.EdgeType.Left));
// Linguistik Kemiringan Jalan
LinguisticVariable lvKemiringan = new LinguisticVariable("Kemiringan", -90, 90);
lvKemiringan.AddLabel(fsTurun);
lvKemiringan.AddLabel(fsDatar);
lvKemiringan.AddLabel(fsNaik);
// OUTPUT
// Tingkat Pengereman (0-10)
FuzzySet fsLemah = new FuzzySet("Lemah", new TrapezoidalFunction(3, 4, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsMedium = new FuzzySet("Sedang", new TrapezoidalFunction(3, 4, 6, 7));
FuzzySet fsKuat = new FuzzySet("Kuat", new TrapezoidalFunction(6, 7, TrapezoidalFunction.EdgeType.Left));
// Linguistik Kecepatan
LinguisticVariable lvTingkatPengereman = new LinguisticVariable("TingkatPengereman", 0, 10);
lvTingkatPengereman.AddLabel(fsLemah);
lvTingkatPengereman.AddLabel(fsMedium);
lvTingkatPengereman.AddLabel(fsKuat);
// Database
Database fuzzyDB = new Database();
fuzzyDB.AddVariable(lvJarak);
fuzzyDB.AddVariable(lvKemiringan);
fuzzyDB.AddVariable(lvKecepatan);
fuzzyDB.AddVariable(lvTingkatPengereman);
// Inferensi System Engine
InferenceSystem IS = new InferenceSystem(fuzzyDB, new CentroidDefuzzifier(1000));
// Rules
IS.NewRule("Rule 1", "IF Kecepatan IS Lambat AND Jarak IS Dekat AND Kemiringan IS Turun THEN TingkatPengereman IS Kuat");
IS.NewRule("Rule 2", "IF Kecepatan IS Lambat AND Jarak IS Dekat AND Kemiringan IS Naik THEN TingkatPengereman IS Lemah");
IS.NewRule("Rule 3", "IF Kecepatan IS Lambat AND Jarak IS Dekat AND Kemiringan IS Datar THEN TingkatPengereman IS Sedang");
IS.NewRule("Rule 4", "IF Kecepatan IS Lambat AND Jarak IS Jauh AND Kemiringan IS Datar THEN TingkatPengereman IS Lemah");
IS.NewRule("Rule 5", "IF Kecepatan IS Lambat AND Jarak IS Jauh AND Kemiringan IS Naik THEN TingkatPengereman IS Lemah");
IS.NewRule("Rule 6", "IF Kecepatan IS Lambat AND Jarak IS Jauh AND Kemiringan IS Turun THEN TingkatPengereman IS Sedang");
IS.NewRule("Rule 7", "IF Kecepatan IS Lambat AND Jarak IS SangatJauh AND Kemiringan IS Datar THEN TingkatPengereman IS Lemah");
IS.NewRule("Rule 8", "IF Kecepatan IS Lambat AND Jarak IS SangatJauh AND Kemiringan IS Naik THEN TingkatPengereman IS Lemah");
IS.NewRule("Rule 9", "IF Kecepatan IS Lambat AND Jarak IS SangatJauh AND Kemiringan IS Turun THEN TingkatPengereman IS Sedang");
IS.NewRule("Rule 10", "IF Kecepatan IS Sedang AND Jarak IS Dekat AND Kemiringan IS Datar THEN TingkatPengereman IS Kuat");
IS.NewRule("Rule 11", "IF Kecepatan IS Sedang AND Jarak IS Dekat AND Kemiringan IS Naik THEN TingkatPengereman IS Sedang");
IS.NewRule("Rule 12", "IF Kecepatan IS Sedang AND Jarak IS Dekat AND Kemiringan IS Turun THEN TingkatPengereman IS Kuat");
IS.NewRule("Rule 13", "IF Kecepatan IS Sedang AND Jarak IS Jauh AND Kemiringan IS Datar THEN TingkatPengereman IS Sedang");
IS.NewRule("Rule 14", "IF Kecepatan IS Sedang AND Jarak IS Jauh AND Kemiringan IS Naik THEN TingkatPengereman IS Lemah");
IS.NewRule("Rule 15", "IF Kecepatan IS Sedang AND Jarak IS Jauh AND Kemiringan IS Turun THEN TingkatPengereman IS Kuat");
IS.NewRule("Rule 16", "IF Kecepatan IS Sedang AND Jarak IS SangatJauh AND Kemiringan IS Datar THEN TingkatPengereman IS Lemah");
IS.NewRule("Rule 17", "IF Kecepatan IS Sedang AND Jarak IS SangatJauh AND Kemiringan IS Naik THEN TingkatPengereman IS Lemah");
IS.NewRule("Rule 18", "IF Kecepatan IS Sedang AND Jarak IS SangatJauh AND Kemiringan IS Turun THEN TingkatPengereman IS Sedang");
IS.NewRule("Rule 19", "IF Kecepatan IS Cepat AND Jarak IS Dekat AND Kemiringan IS Datar THEN TingkatPengereman IS Kuat");
IS.NewRule("Rule 20", "IF Kecepatan IS Cepat AND Jarak IS Dekat AND Kemiringan IS Naik THEN TingkatPengereman IS Sedang");
IS.NewRule("Rule 21", "IF Kecepatan IS Cepat AND Jarak IS Dekat AND Kemiringan IS Turun THEN TingkatPengereman IS Kuat");
IS.NewRule("Rule 22", "IF Kecepatan IS Cepat AND Jarak IS Jauh AND Kemiringan IS Datar THEN TingkatPengereman IS Kuat");
IS.NewRule("Rule 23", "IF Kecepatan IS Cepat AND Jarak IS Jauh AND Kemiringan IS Naik THEN TingkatPengereman IS Sedang");
IS.NewRule("Rule 24", "IF Kecepatan IS Cepat AND Jarak IS Jauh AND Kemiringan IS Turun THEN TingkatPengereman IS Kuat");
IS.NewRule("Rule 25", "IF Kecepatan IS Cepat AND Jarak IS SangatJauh AND Kemiringan IS Datar THEN TingkatPengereman IS Sedang");
IS.NewRule("Rule 26", "IF Kecepatan IS Cepat AND Jarak IS SangatJauh AND Kemiringan IS Naik THEN TingkatPengereman IS Lemah");
IS.NewRule("Rule 27", "IF Kecepatan IS Cepat AND Jarak IS SangatJauh AND Kemiringan IS Turun THEN TingkatPengereman IS Kuat");
// Set Input
IS.SetInput("Kecepatan", (float)speed);
IS.SetInput("Jarak", (float)distance);
IS.SetInput("Kemiringan", (float)angle);
// Get output
double BreakLevel = IS.Evaluate("TingkatPengereman");
// Tampilkan Hasil
System.Console.WriteLine(BreakLevel);
}
private static InferenceSystem CreateInferenceSystem()
{
var objectiveVariable = new LinguisticVariable("OBJECTIVE", 0, 1);
var subjectiveVariable = new LinguisticVariable("SUBJECTIVE", 0, 1);
var algorithmScoreVariable = new LinguisticVariable("ALGORITHM_SCORE", 0, 1);
var objectiveLow = new ZTypeMembership(0, 0.5);
var objectiveMedium = new PITypeMembership(0, 0.5, 0.75);
var objectiveHigh = new STypeMembership(0.25, 1);
var subjectiveLow = new ZTypeMembership(0, 0.5);
var subjectiveMedium = new PITypeMembership(0.25, 0.5, 0.75);
var subjectiveHigh = new STypeMembership(0.5, 1);
var algorithmScoreVeryLow = new VeryHedge(new ZTypeMembership(0, 0.5));
var algorithmScoreLow = new ZTypeMembership(0, 0.5);
var algorithmScoreMedium = new PITypeMembership(0.25, 0.5, 0.75);
var algorithmScoreHigh = new STypeMembership(0.5, 1);
var algorithmScoreVeryHigh = new VeryHedge(new STypeMembership(0.5, 1));
var objectiveLowSet = new FuzzySet("LOW", objectiveLow);
var objectiveMediumSet = new FuzzySet("MEDIUM", objectiveMedium);
var objectiveHighSet = new FuzzySet("HIGH", objectiveHigh);
var subjectiveLowSet = new FuzzySet("LOW", subjectiveLow);
var subjectiveMediumSet = new FuzzySet("MEDIUM", subjectiveMedium);
var subjectiveHighSet = new FuzzySet("HIGH", subjectiveHigh);
var resultVeryLowSet = new FuzzySet("VERY_LOW", algorithmScoreVeryLow);
var resultLowSet = new FuzzySet("LOW", algorithmScoreLow);
var resultMediumSet = new FuzzySet("MEDIUM", algorithmScoreMedium);
var resultHighSet = new FuzzySet("HIGH", algorithmScoreHigh);
var resultVeryHighSet = new FuzzySet("VERY_HIGH", algorithmScoreVeryHigh);
objectiveVariable.AddLabel(objectiveLowSet);
objectiveVariable.AddLabel(objectiveMediumSet);
objectiveVariable.AddLabel(objectiveHighSet);
subjectiveVariable.AddLabel(subjectiveLowSet);
subjectiveVariable.AddLabel(subjectiveMediumSet);
subjectiveVariable.AddLabel(subjectiveHighSet);
algorithmScoreVariable.AddLabel(resultVeryLowSet);
algorithmScoreVariable.AddLabel(resultLowSet);
algorithmScoreVariable.AddLabel(resultMediumSet);
algorithmScoreVariable.AddLabel(resultHighSet);
algorithmScoreVariable.AddLabel(resultVeryHighSet);
var rulebase = new Database();
rulebase.AddVariable(objectiveVariable);
rulebase.AddVariable(subjectiveVariable);
rulebase.AddVariable(algorithmScoreVariable);
var inferenceSystem = new InferenceSystem(rulebase, new CentroidDefuzzifier(30));
inferenceSystem.NewRule("Rule1", "if OBJECTIVE is LOW and SUBJECTIVE is LOW then ALGORITHM_SCORE is VERY_LOW ");
inferenceSystem.NewRule("Rule2", "if OBJECTIVE is LOW and SUBJECTIVE is MEDIUM then ALGORITHM_SCORE is LOW");
inferenceSystem.NewRule("Rule3", "if OBJECTIVE is LOW and SUBJECTIVE is HIGH then ALGORITHM_SCORE is MEDIUM");
inferenceSystem.NewRule("Rule4", "if OBJECTIVE is MEDIUM and SUBJECTIVE is LOW then ALGORITHM_SCORE is LOW");
inferenceSystem.NewRule("Rule5", "if OBJECTIVE is MEDIUM and SUBJECTIVE is MEDIUM then ALGORITHM_SCORE is MEDIUM");
inferenceSystem.NewRule("Rule6", "if OBJECTIVE is MEDIUM and SUBJECTIVE is HIGH then ALGORITHM_SCORE is HIGH");
inferenceSystem.NewRule("Rule7", "if OBJECTIVE is HIGH and SUBJECTIVE is LOW then ALGORITHM_SCORE is MEDIUM");
inferenceSystem.NewRule("Rule8", "if OBJECTIVE is HIGH and SUBJECTIVE is MEDIUM then ALGORITHM_SCORE is HIGH");
inferenceSystem.NewRule("Rule9", "if OBJECTIVE is HIGH and SUBJECTIVE is HIGH then ALGORITHM_SCORE is VERY_HIGH");
return(inferenceSystem);
}
void InitCuckoo()
{
openFileDialog1.InitialDirectory = @"D:\YandexDisk\Программирование\GestureRecognize\GestureRecognize\bin\Debug";
if (openFileDialog1.ShowDialog() == DialogResult.OK)
{
BinaryFormatter bf = new BinaryFormatter();
using (FileStream fs = File.OpenRead(openFileDialog1.FileName))
{
scopes = (Scope[])bf.Deserialize(fs);
}
}
deltaRMS = new LingVar(0, "deltarms", -4f, 23, scopes, nums);
Turns0 = new LingVar(1, "turns0", 0, 175, scopes, nums);
Zeros0 = new LingVar(2, "zeros0", 14, 80, scopes, nums);
Turns1 = new LingVar(3, "turns1", 0, 175, scopes, nums);
Zeros1 = new LingVar(4, "zeros1", 14, 80, scopes, nums);
const int numOutTerms = 10;
output = new LingVar("out", numOutTerms, 1, numOutTerms, 1f);
fuzzyDB = new Database();
fuzzyDB.AddVariable(deltaRMS.lv);
fuzzyDB.AddVariable(Turns0.lv);
fuzzyDB.AddVariable(Turns1.lv);
fuzzyDB.AddVariable(Zeros0.lv);
fuzzyDB.AddVariable(Zeros1.lv);
fuzzyDB.AddVariable(output.lv);
loadDataOnly();
IS = new InferenceSystem(fuzzyDB, new CentroidDefuzzifier(CentrDefu));
string rule = "";
for (int i = 0; i < nums.Length; i++)
{
rule = "IF deltarms IS " + deltaRMS.terms[i].Name;
rule += " AND turns0 IS " + Turns0.terms[i].Name;
rule += " AND turns1 IS " + Turns1.terms[i].Name;
rule += " AND zeros0 IS " + Zeros0.terms[i].Name;
rule += " AND zeros1 IS " + Zeros1.terms[i].Name;
rule += " THEN out IS " + output.terms[i].Name;
IS.NewRule(i.ToString(), rule);
}
//chart.RangeX = new AForge.Range(14, 80);
//chart.AddDataSeries("0", Color.Black, AForge.Controls.Chart.SeriesType.Line, 3, true);
//chart.AddDataSeries("1", Color.Red, AForge.Controls.Chart.SeriesType.Line, 3, true);
//chart.AddDataSeries("2", Color.Blue, AForge.Controls.Chart.SeriesType.Line, 3, true);
//chart.AddDataSeries("3", Color.Green, AForge.Controls.Chart.SeriesType.Line, 3, true);
//chart.AddDataSeries("4", Color.Pink, AForge.Controls.Chart.SeriesType.Line, 3, true);
//chart.AddDataSeries("5", Color.Purple, AForge.Controls.Chart.SeriesType.Line, 3, true);
//chart.AddDataSeries("6", Color.Orange, AForge.Controls.Chart.SeriesType.Line, 3, true);
//chart.AddDataSeries("7", Color.Yellow, AForge.Controls.Chart.SeriesType.Line, 3, true);
//chart.AddDataSeries("8", Color.Lime, AForge.Controls.Chart.SeriesType.Line, 3, true);
//chart.AddDataSeries("9", Color.Coral, AForge.Controls.Chart.SeriesType.Line, 3, true);
//// get membership of some points to the cool fuzzy set
//double[][,] chartValues = new double[10][,];
//for (int i = 0; i < 10; i++)
// chartValues[i] = new double[140, 2];
//// showing the shape of the linguistic variable - the shape of its labels memberships from start to end
//int j = 0;
//for (float x = 14; x < 80; x += 0.5f, j++)
//{
// double[] ys = new double[10];
// for (int m = 0; m < 10; m++)
// {
// //ys[m] = deltaRMS.lv.GetLabelMembership("deltarms" + (m*6).ToString(), x);
// ys[m] = Zeros0.lv.GetLabelMembership("zeros0" + (m * 6).ToString(), x);
// }
// for (int m = 0; m < 10; m++)
// {
// chartValues[m][j, 0] = x;
// chartValues[m][j, 1] = ys[m];
// }
//}
//// plot membership to a chart
//for (int m = 0; m < 10; m++)
//{
// chart.UpdateDataSeries(m.ToString(), chartValues[m]);
//}
}
// Hardcode initializing the Fuzzy Inference System
void InitFuzzyEngine( )
{
// Linguistic labels (fuzzy sets) that compose the distances
FuzzySet fsNear = new FuzzySet("Near", new TrapezoidalFunction(15, 50, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsMedium = new FuzzySet("Medium", new TrapezoidalFunction(15, 50, 60, 100));
FuzzySet fsFar = new FuzzySet("Far", new TrapezoidalFunction(60, 100, TrapezoidalFunction.EdgeType.Left));
// Right Distance (Input)
LinguisticVariable lvRight = new LinguisticVariable("RightDistance", 0, 120);
lvRight.AddLabel(fsNear);
lvRight.AddLabel(fsMedium);
lvRight.AddLabel(fsFar);
// Left Distance (Input)
LinguisticVariable lvLeft = new LinguisticVariable("LeftDistance", 0, 120);
lvLeft.AddLabel(fsNear);
lvLeft.AddLabel(fsMedium);
lvLeft.AddLabel(fsFar);
// Front Distance (Input)
LinguisticVariable lvFront = new LinguisticVariable("FrontalDistance", 0, 120);
lvFront.AddLabel(fsNear);
lvFront.AddLabel(fsMedium);
lvFront.AddLabel(fsFar);
// Linguistic labels (fuzzy sets) that compose the angle
FuzzySet fsVN = new FuzzySet("VeryNegative", new TrapezoidalFunction(-40, -35, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsN = new FuzzySet("Negative", new TrapezoidalFunction(-40, -35, -25, -20));
FuzzySet fsLN = new FuzzySet("LittleNegative", new TrapezoidalFunction(-25, -20, -10, -5));
FuzzySet fsZero = new FuzzySet("Zero", new TrapezoidalFunction(-10, 5, 5, 10));
FuzzySet fsLP = new FuzzySet("LittlePositive", new TrapezoidalFunction(5, 10, 20, 25));
FuzzySet fsP = new FuzzySet("Positive", new TrapezoidalFunction(20, 25, 35, 40));
FuzzySet fsVP = new FuzzySet("VeryPositive", new TrapezoidalFunction(35, 40, TrapezoidalFunction.EdgeType.Left));
// Angle
LinguisticVariable lvAngle = new LinguisticVariable("Angle", -50, 50);
lvAngle.AddLabel(fsVN);
lvAngle.AddLabel(fsN);
lvAngle.AddLabel(fsLN);
lvAngle.AddLabel(fsZero);
lvAngle.AddLabel(fsLP);
lvAngle.AddLabel(fsP);
lvAngle.AddLabel(fsVP);
// The database
Database fuzzyDB = new Database( );
fuzzyDB.AddVariable(lvFront);
fuzzyDB.AddVariable(lvLeft);
fuzzyDB.AddVariable(lvRight);
fuzzyDB.AddVariable(lvAngle);
// Creating the inference system
IS = new InferenceSystem(fuzzyDB, new CentroidDefuzzifier(1000));
// Going Straight
IS.NewRule("Rule 1", "IF FrontalDistance IS Far THEN Angle IS Zero");
// Going Straight (if can go anywhere)
IS.NewRule("Rule 2", "IF FrontalDistance IS Far AND RightDistance IS Far AND LeftDistance IS Far THEN Angle IS Zero");
// Near right wall
IS.NewRule("Rule 3", "IF RightDistance IS Near AND LeftDistance IS Not Near THEN Angle IS LittleNegative");
// Near left wall
IS.NewRule("Rule 4", "IF RightDistance IS Not Near AND LeftDistance IS Near THEN Angle IS LittlePositive");
// Near front wall - room at right
IS.NewRule("Rule 5", "IF RightDistance IS Far AND FrontalDistance IS Near THEN Angle IS Positive");
// Near front wall - room at left
IS.NewRule("Rule 6", "IF LeftDistance IS Far AND FrontalDistance IS Near THEN Angle IS Negative");
// Near front wall - room at both sides - go right
IS.NewRule("Rule 7", "IF RightDistance IS Far AND LeftDistance IS Far AND FrontalDistance IS Near THEN Angle IS Positive");
}
public void FromValenceArousalToEmotions(List <double> Valence, List <double> Arousal)
{
int meanValence = Mean(Valence);
int meanArousal = Mean(Arousal);
int sValence = (int)Math.Sqrt(Var(Valence)) + 1;
int sArousal = (int)Math.Sqrt(Var(Arousal)) + 1;
ResLogFlou2Label.Text = "Traitement en cours";
ResLogFlou2Label.Refresh();
//OK ne pas toucher
#region Input (Valence)
var lvValence = new LinguisticVariable("Valence", meanValence - 10 * sValence, meanValence + 10 * sValence);
var fsVeryLow = new FuzzySet("VeryLow", new TrapezoidalFunction(0, 3, 6));
var fsLow = new FuzzySet("Low", new TrapezoidalFunction(6, 7, 8));
var fsMidLow = new FuzzySet("MidLow", new TrapezoidalFunction(8, 9, 10));
var fsMid = new FuzzySet("Mid", new TrapezoidalFunction(10, 15, 20));
var fsMidHigh = new FuzzySet("MidHigh", new TrapezoidalFunction(20, 22, 24));
var fsHigh = new FuzzySet("High", new TrapezoidalFunction(24, 25, 26));
var fsVeryHigh = new FuzzySet("VeryHigh", new TrapezoidalFunction(26, 28, 30));
var fsVeryLowValence = new FuzzySet("VeryLow", new TrapezoidalFunction(meanValence - 10 * sValence, meanValence - 8 * sValence, meanValence - 5 * sValence));
var fsLowValence = new FuzzySet("Low", new TrapezoidalFunction(meanValence - 5 * sValence, meanValence - 4 * sValence, meanValence - 3 * sValence));
var fsMidLowValence = new FuzzySet("MidLow", new TrapezoidalFunction(meanValence - 3 * sValence, meanValence - 2 * sValence, meanValence));
var fsMidHighValence = new FuzzySet("MidHigh", new TrapezoidalFunction(meanValence, meanValence + 2 * sValence, meanValence + 3 * sValence));
var fsHighValence = new FuzzySet("High", new TrapezoidalFunction(meanValence + 3 * sValence, meanValence + 4 * sValence, meanValence + 5 * sValence));
var fsVeryHighValence = new FuzzySet("VeryHigh", new TrapezoidalFunction(meanValence + 5 * sValence, meanValence + 8 * sValence, meanValence + 10 * sValence));
lvValence.AddLabel(fsVeryLowValence);
lvValence.AddLabel(fsLowValence);
lvValence.AddLabel(fsMidLowValence);
lvValence.AddLabel(fsMidHighValence);
lvValence.AddLabel(fsHighValence);
lvValence.AddLabel(fsVeryHighValence);
#endregion
#region Input (Arousal)
var lvArousal = new LinguisticVariable("Arousal", meanArousal - 10 * sArousal, meanArousal + 10 * sArousal);
var fsVeryLowArousal = new FuzzySet("VeryLow", new TrapezoidalFunction(meanArousal - 10 * sArousal, meanArousal - 8 * sArousal, meanArousal - 5 * sArousal));
var fsLowArousal = new FuzzySet("Low", new TrapezoidalFunction(meanArousal - 5 * sArousal, meanArousal - 4 * sArousal, meanArousal - 3 * sArousal));
var fsMidLowArousal = new FuzzySet("MidLow", new TrapezoidalFunction(meanArousal - 3 * sArousal, meanArousal - 2 * sArousal, meanArousal));
var fsMidHighArousal = new FuzzySet("MidHigh", new TrapezoidalFunction(meanArousal, meanArousal + 2 * sArousal, meanArousal + 3 * sArousal));
var fsHighArousal = new FuzzySet("High", new TrapezoidalFunction(meanArousal + 3 * sArousal, meanArousal + 4 * sArousal, meanArousal + 5 * sArousal));
var fsVeryHighArousal = new FuzzySet("VeryHigh", new TrapezoidalFunction(meanArousal + 5 * sArousal, meanArousal + 8 * sArousal, meanArousal + 10 * sArousal));
lvArousal.AddLabel(fsVeryLowArousal);
lvArousal.AddLabel(fsLowArousal);
lvArousal.AddLabel(fsMidLowArousal);
lvArousal.AddLabel(fsMidHighArousal);
lvArousal.AddLabel(fsHighArousal);
lvArousal.AddLabel(fsVeryHighArousal);
#endregion
//il y a l'output à faire, je sais pas exactement comment il faut faire, à checker en dessous c'est peut etre de la connerie que j'ai fait
#region Output (Boredom)
var lvBoredom = new LinguisticVariable("Boredom", 0, 30);
//var fsVeryLow = new FuzzySet("VeryLow", new TrapezoidalFunction(0, 3, 6));
//var fsLow = new FuzzySet("Low", new TrapezoidalFunction(6, 7, 8));
//var fsMidLow = new FuzzySet("MidLow", new TrapezoidalFunction(8, 9, 10));
//var fsMid = new FuzzySet("Mid", new TrapezoidalFunction(10, 15, 20));
//var fsMidHigh = new FuzzySet("MidHigh", new TrapezoidalFunction(20, 22, 24));
//var fsHigh = new FuzzySet("High", new TrapezoidalFunction(24, 25, 26));
//var fsVeryHigh = new FuzzySet("VeryHigh", new TrapezoidalFunction(26, 28, 30));
lvBoredom.AddLabel(fsVeryLow);
lvBoredom.AddLabel(fsLow);
lvBoredom.AddLabel(fsMidLow);
lvBoredom.AddLabel(fsMid);
lvBoredom.AddLabel(fsMidHigh);
lvBoredom.AddLabel(fsHigh);
lvBoredom.AddLabel(fsVeryHigh);
#endregion
#region Output (Challenge)
var lvChallenge = new LinguisticVariable("Challenge", 0, 30);
//var fsVeryLow = new FuzzySet("VeryLow", new TrapezoidalFunction(0, 3, 6));
//var fsLow = new FuzzySet("Low", new TrapezoidalFunction(6, 7, 8));
//var fsMidLow = new FuzzySet("MidLow", new TrapezoidalFunction(8, 9, 10));
//var fsMid = new FuzzySet("Mid", new TrapezoidalFunction(10, 15, 20));
//var fsMidHigh = new FuzzySet("MidHigh", new TrapezoidalFunction(20, 22, 24));
//var fsHigh = new FuzzySet("High", new TrapezoidalFunction(24, 25, 26));
//var fsVeryHigh = new FuzzySet("VeryHigh", new TrapezoidalFunction(26, 28, 30));
lvChallenge.AddLabel(fsVeryLow);
lvChallenge.AddLabel(fsLow);
lvChallenge.AddLabel(fsMidLow);
lvChallenge.AddLabel(fsMid);
lvChallenge.AddLabel(fsMidHigh);
lvChallenge.AddLabel(fsHigh);
lvChallenge.AddLabel(fsVeryHigh);
#endregion
#region Output (Excitement)
var lvExcitement = new LinguisticVariable("Excitement", 0, 30);
//var fsVeryLow = new FuzzySet("VeryLow", new TrapezoidalFunction(0, 3, 6));
//var fsLow = new FuzzySet("Low", new TrapezoidalFunction(6, 7, 8));
//var fsMidLow = new FuzzySet("MidLow", new TrapezoidalFunction(8, 9, 10));
//var fsMid = new FuzzySet("Mid", new TrapezoidalFunction(10, 15, 20));
//var fsMidHigh = new FuzzySet("MidHigh", new TrapezoidalFunction(20, 22, 24));
//var fsHigh = new FuzzySet("High", new TrapezoidalFunction(24, 25, 26));
//var fsVeryHigh = new FuzzySet("VeryHigh", new TrapezoidalFunction(26, 28, 30));
lvExcitement.AddLabel(fsVeryLow);
lvExcitement.AddLabel(fsLow);
lvExcitement.AddLabel(fsMidLow);
lvExcitement.AddLabel(fsMid);
lvExcitement.AddLabel(fsMidHigh);
lvExcitement.AddLabel(fsHigh);
lvExcitement.AddLabel(fsVeryHigh);
#endregion
#region Output (Frustration)
var lvFrustration = new LinguisticVariable("Frustration", 0, 30);
//var fsVeryLow = new FuzzySet("VeryLow", new TrapezoidalFunction(0, 3, 6));
//var fsLow = new FuzzySet("Low", new TrapezoidalFunction(6, 7, 8));
//var fsMidLow = new FuzzySet("MidLow", new TrapezoidalFunction(8, 9, 10));
//var fsMid = new FuzzySet("Mid", new TrapezoidalFunction(10, 15, 20));
//var fsMidHigh = new FuzzySet("MidHigh", new TrapezoidalFunction(20, 22, 24));
//var fsHigh = new FuzzySet("High", new TrapezoidalFunction(24, 25, 26));
//var fsVeryHigh = new FuzzySet("VeryHigh", new TrapezoidalFunction(26, 28, 30));
lvFrustration.AddLabel(fsVeryLow);
lvFrustration.AddLabel(fsLow);
lvFrustration.AddLabel(fsMidLow);
lvFrustration.AddLabel(fsMid);
lvFrustration.AddLabel(fsMidHigh);
lvFrustration.AddLabel(fsHigh);
lvFrustration.AddLabel(fsVeryHigh);
#endregion
#region Output (Fun)
var lvFun = new LinguisticVariable("Fun", 0, 30);
//var fsVeryLow = new FuzzySet("VeryLow", new TrapezoidalFunction(0, 3, 6));
//var fsLow = new FuzzySet("Low", new TrapezoidalFunction(6, 7, 8));
//var fsMidLow = new FuzzySet("MidLow", new TrapezoidalFunction(8, 9, 10));
//var fsMid = new FuzzySet("Mid", new TrapezoidalFunction(10, 15, 20));
//var fsMidHigh = new FuzzySet("MidHigh", new TrapezoidalFunction(20, 22, 24));
//var fsHigh = new FuzzySet("High", new TrapezoidalFunction(24, 25, 26));
//var fsVeryHigh = new FuzzySet("VeryHigh", new TrapezoidalFunction(26, 28, 30));
lvFun.AddLabel(fsVeryLow);
lvFun.AddLabel(fsLow);
lvFun.AddLabel(fsMidLow);
lvFun.AddLabel(fsMid);
lvFun.AddLabel(fsMidHigh);
lvFun.AddLabel(fsHigh);
lvFun.AddLabel(fsVeryHigh);
#endregion
#region Système Inference
var fuzzyDb = new Database();
//2 inputs : valence et arousal
fuzzyDb.AddVariable(lvValence);
fuzzyDb.AddVariable(lvArousal);
//5 outputs : boredom, challenge, excitement, frustration, and fun
fuzzyDb.AddVariable(lvBoredom);
fuzzyDb.AddVariable(lvChallenge);
fuzzyDb.AddVariable(lvExcitement);
fuzzyDb.AddVariable(lvFrustration);
fuzzyDb.AddVariable(lvFun);
// Creation system inference
// Initialise la methode de défuzzification : centre de gravité
var inferenceSys = new InferenceSystem(fuzzyDb, new CentroidDefuzzifier(1000));
// Ajout des regles
inferenceSys.NewRule("Rule 23", "IF Arousal IS NOT VeryLow AND Valence IS MidHigh THEN Fun IS Low");
inferenceSys.NewRule("Rule 24", "IF Arousal IS NOT Low AND Valence IS MidHigh THEN Fun IS Low");
inferenceSys.NewRule("Rule 25", "IF Arousal IS NOT VeryLow AND Valence IS High THEN Fun IS Mid");
inferenceSys.NewRule("Rule 26", "IF Valence IS VeryHigh THEN Fun IS High");
inferenceSys.NewRule("Rule 27", "IF Arousal IS MidHigh AND Valence IS MidLow THEN Challenge IS Low");
inferenceSys.NewRule("Rule 28", "IF Arousal IS MidHigh AND Valence IS MidHigh THEN Challenge IS Low");
inferenceSys.NewRule("Rule 29", "IF Arousal IS High AND Valence IS MidLow THEN Challenge IS Mid");
inferenceSys.NewRule("Rule 30", "IF Arousal IS High AND Valence IS MidHigh THEN Challenge IS Mid");
inferenceSys.NewRule("Rule 31", "IF Arousal IS VeryHigh AND Valence IS MidLow THEN Challenge IS High");
inferenceSys.NewRule("Rule 32", "IF Arousal IS VeryHigh AND Valence IS MidHigh THEN Challenge IS High");
inferenceSys.NewRule("Rule 33", "IF Arousal IS MidLow AND Valence IS MidLow THEN Boredom IS Low");
inferenceSys.NewRule("Rule 34", "IF Arousal IS MidLow AND Valence IS Low THEN Boredom IS Mid");
inferenceSys.NewRule("Rule 35", "IF Arousal IS Low AND Valence IS Low THEN Boredom IS Mid");
inferenceSys.NewRule("Rule 36", "IF Arousal IS Low AND Valence IS MidLow THEN Boredom IS Mid");
inferenceSys.NewRule("Rule 37", "IF Arousal IS MidLow AND Valence IS VeryLow THEN Boredom IS High");
inferenceSys.NewRule("Rule 38", "IF Arousal IS Low AND Valence IS VeryLow THEN Boredom IS High");
inferenceSys.NewRule("Rule 39", "IF Arousal IS VeryLow AND Valence IS VeryLow THEN Boredom IS High");
inferenceSys.NewRule("Rule 40", "IF Arousal IS VeryLow AND Valence IS Low THEN Boredom IS High");
inferenceSys.NewRule("Rule 41", "IF Arousal IS VeryLow AND Valence IS MidLow THEN Boredom IS High");
inferenceSys.NewRule("Rule 42", "IF Arousal IS VeryHigh AND Valence IS MidLow THEN Frustration IS High");
inferenceSys.NewRule("Rule 43", "IF Arousal IS MidHigh AND Valence IS Low THEN Frustration IS Mid");
inferenceSys.NewRule("Rule 44", "IF Arousal IS High AND Valence IS Low THEN Frustration IS Mid");
inferenceSys.NewRule("Rule 45", "IF Arousal IS High AND Valence IS MidLow THEN Frustration IS Mid");
inferenceSys.NewRule("Rule 46", "IF Arousal IS MidHigh AND Valence IS VeryLow THEN Frustration IS High");
inferenceSys.NewRule("Rule 47", "IF Arousal IS High AND Valence IS VeryLow THEN Frustration IS High");
inferenceSys.NewRule("Rule 48", "IF Arousal IS VeryHigh AND Valence IS VeryLow THEN Frustration IS High");
inferenceSys.NewRule("Rule 49", "IF Arousal IS VeryHigh AND Valence IS Low THEN Frustration IS High");
inferenceSys.NewRule("Rule 50", "IF Arousal IS VeryHigh AND Valence IS MidLow THEN Frustration IS High");
inferenceSys.NewRule("Rule 51", "IF Arousal IS VeryLow AND Valence IS VeryLow THEN Challenge IS VeryLow");
inferenceSys.NewRule("Rule 52", "IF Arousal IS Low AND Valence IS VeryLow THEN Challenge IS VeryLow");
inferenceSys.NewRule("Rule 53", "IF Valence IS High THEN Challenge IS VeryLow");
inferenceSys.NewRule("Rule 53b", "IF Valence IS High THEN Boredom IS VeryLow");
inferenceSys.NewRule("Rule 53c", "IF Valence IS High THEN Frustration IS VeryLow");
inferenceSys.NewRule("Rule 54", "IF Valence IS VeryHigh THEN Challenge IS VeryLow");
inferenceSys.NewRule("Rule 54b", "IF Valence IS VeryHigh THEN Boredom IS VeryLow ");
inferenceSys.NewRule("Rule 54c", "IF Valence IS VeryHigh THEN Frustration IS VeryLow ");
inferenceSys.NewRule("Rule 55", "IF Valence IS MidHigh THEN Boredom IS VeryLow");
inferenceSys.NewRule("Rule 55b", "IF Valence IS MidHigh THEN Frustration IS VeryLow");
inferenceSys.NewRule("Rule 56", "IF Arousal IS VeryLow THEN Challenge IS VeryLow");
inferenceSys.NewRule("Rule 56b", "IF Arousal IS VeryLow THEN Frustration IS VeryLow");
inferenceSys.NewRule("Rule 57", "IF Arousal IS Low THEN Challenge IS VeryLow");
inferenceSys.NewRule("Rule 57b", "IF Arousal IS Low THEN Frustration IS VeryLow");
inferenceSys.NewRule("Rule 58", "IF Arousal IS MidLow THEN Challenge IS VeryLow");
inferenceSys.NewRule("Rule 58b", "IF Arousal IS MidLow THEN Frustration IS VeryLow");
inferenceSys.NewRule("Rule 59", "IF Arousal IS MidHigh THEN Boredom IS VeryLow");
inferenceSys.NewRule("Rule 60", "IF Arousal IS High THEN Boredom IS VeryLow");
inferenceSys.NewRule("Rule 61", "IF Arousal IS VeryHigh THEN Boredom IS VeryLow");
inferenceSys.NewRule("Rule 62", "IF Arousal IS VeryLow AND Valence IS MidHigh THEN Fun IS VeryLow");
inferenceSys.NewRule("Rule 63", "IF Arousal IS Low AND Valence IS MidHigh THEN Fun IS VeryLow");
inferenceSys.NewRule("Rule 64", "IF Arousal IS VeryLow AND Valence IS High THEN Fun IS Low");
inferenceSys.NewRule("Rule 65", "IF Valence IS MidLow THEN Fun IS VeryLow");
inferenceSys.NewRule("Rule 66", "IF Arousal IS VeryLow AND Valence IS High THEN Boredom IS Low");
inferenceSys.NewRule("Rule 67", "IF Arousal IS Low AND Valence IS MidHigh THEN Boredom IS Low");
inferenceSys.NewRule("Rule 68", "IF Arousal IS VeryLow AND Valence IS MidHigh THEN Boredom IS Mid");
inferenceSys.NewRule("Rule 69", "IF Arousal IS VeryHigh AND Valence IS VeryLow THEN Challenge IS Mid");
inferenceSys.NewRule("Rule 70", "IF Arousal IS VeryHigh AND Valence IS VeryHigh THEN Challenge IS Mid");
inferenceSys.NewRule("Rule 71", "IF Arousal IS High AND Valence IS Low THEN Challenge IS Low");
inferenceSys.NewRule("Rule 72", "IF Arousal IS High AND Valence IS High THEN Challenge IS Low");
inferenceSys.NewRule("Rule 73", "IF Arousal IS VeryHigh AND Valence IS Low THEN Challenge IS High");
inferenceSys.NewRule("Rule 74", "IF Arousal IS VeryHigh AND Valence IS High THEN Challenge IS High");
inferenceSys.NewRule("Rule 75", "IF Arousal IS MidHigh AND Valence IS MidHigh THEN Excitement IS Low");
inferenceSys.NewRule("Rule 76", "IF Arousal IS High AND Valence IS MidHigh THEN Excitement IS Mid");
inferenceSys.NewRule("Rule 77", "IF Arousal IS High AND Valence IS High THEN Excitement IS Mid");
inferenceSys.NewRule("Rule 78", "IF Arousal IS MidHigh AND Valence IS High THEN Excitement IS Mid");
inferenceSys.NewRule("Rule 79", "IF Arousal IS VeryHigh AND Valence IS MidHigh THEN Excitement IS High");
inferenceSys.NewRule("Rule 80", "IF Arousal IS VeryHigh AND Valence IS High THEN Excitement IS High");
inferenceSys.NewRule("Rule 81", "IF Arousal IS VeryHigh AND Valence IS VeryHigh THEN Excitement IS High");
inferenceSys.NewRule("Rule 82", "IF Arousal IS High AND Valence IS VeryHigh THEN Excitement IS High");
inferenceSys.NewRule("Rule 83", "IF Arousal IS MidHigh AND Valence IS VeryHigh THEN Excitement IS High");
inferenceSys.NewRule("Rule 83b", "IF Arousal IS MidLow THEN Excitement IS VeryLow");
inferenceSys.NewRule("Rule 84", "IF Arousal IS MidLow THEN Excitement IS VeryLow");
inferenceSys.NewRule("Rule 85", "IF Arousal IS Low THEN Excitement IS VeryLow");
inferenceSys.NewRule("Rule 86", "IF Arousal IS VeryLow THEN Excitement IS VeryLow");
inferenceSys.NewRule("Rule 87", "IF Valence IS VeryLow THEN Excitement IS VeryLow");
inferenceSys.NewRule("Rule 88", "IF Valence IS Low THEN Excitement IS VeryLow");
inferenceSys.NewRule("Rule 89", "IF Valence IS MidLow THEN Excitement IS VeryLow");
#endregion
#region Exemple
//Pour toutes les valeurs des listes
float valValence = -1f, valArousal = -1f;
for (int i = 0; i < Valence.Count; i++)
{
valValence = (float)Valence[i];
valArousal = (float)Arousal[i];
// Initialise les données d'entrées
inferenceSys.SetInput("Valence", valValence);
inferenceSys.SetInput("Arousal", valArousal);
// Evalue les données de sortie : Boredom, Challenge, Excitement, Frustration, Fun
var resBoredom = -1f;
var resChallenge = -1f;
var resExcitement = -1f;
var resFrustration = -1f;
var resFun = -1f;
try
{
resBoredom = inferenceSys.Evaluate("Boredom");
resChallenge = inferenceSys.Evaluate("Challenge");
resExcitement = inferenceSys.Evaluate("Excitement");
resFrustration = inferenceSys.Evaluate("Frustration");
resFun = inferenceSys.Evaluate("Fun");
ResLogFlou2Label.Text = "" + i + "/" + Valence.Count + "_ Valence: " + valValence + " + Arousal: " + valArousal + " = Boredom: " + resBoredom + ", Challenge: " + resChallenge + ", Excitement: " + resExcitement + ", Frustration: " + resFrustration + ", Fun: " + resFun;
//resFun = inferenceSys.Evaluate("Fun");
//ResLogFlou2Label.Text = ""+i+"/"+Valence.Count+"_ Valence: " + valValence + " + Arousal: " +
// valArousal + " = Boredom: " + resBoredom + ", Challenge: " + resChallenge + ", Excitement: " +
// resExcitement + ", Frustration: " + resFrustration + ", Fun: " + resFun;
ResLogFlou2Label.Refresh();
//Stockage des résultats dans la liste adéquate au résultat
Boredom.Add((double)resBoredom);
Challenge.Add((double)resChallenge);
Excitement.Add((double)resExcitement);
Frustration.Add((double)resFrustration);
Fun.Add((double)resFun);
}
catch (Exception ex)
{
ResLogFlou2Label.Text = "" + i;
ResLogFlou2Label.Refresh();
throw new Exception(string.Format("Erreur : {0}", ex.Message));
Boredom.Add(0);
Challenge.Add(0);
Excitement.Add(0);
Frustration.Add(0);
Fun.Add(0);
}
DataWriter(Boredom, Challenge, Excitement, Frustration, Fun);
}
#endregion
}