public LingVar(string name, int numTerms, float min, float max, float cross)
{
this.min = min;
this.max = max;
range = Math.Abs(max - min);
float left, right, center;
terms = new FuzzySet[numTerms];
lv = new LinguisticVariable(name, min, max);
center = min + 0 * range / (numTerms - 1) * (1 / cross);
right = min + (0 + 1) * range / (numTerms - 1) * (1 / cross);
terms[0] = new FuzzySet(name + "-0", new TrapezoidalFunction(center, right, TrapezoidalFunction.EdgeType.Right));
lv.AddLabel(terms[0]);
for (int i = 1; i < numTerms - 1; i++)
{
left = min + (i - 1) * range / (numTerms - 1) * (1 / cross);
center = min + i * range / (numTerms - 1) * (1 / cross);
right = min + (i + 1) * range / (numTerms - 1) * (1 / cross);
terms[i] = new FuzzySet(name + "-" + i.ToString(), new TrapezoidalFunction(left, center, right));
lv.AddLabel(terms[i]);
}
left = min + (numTerms - 1 - 1) * range / (numTerms - 1) * (1 / cross);
center = min + (numTerms - 1) * range / (numTerms - 1) * (1 / cross);
terms[numTerms - 1] = new FuzzySet(name + "-" + (numTerms - 1).ToString(), new TrapezoidalFunction(left, center, TrapezoidalFunction.EdgeType.Left));
lv.AddLabel(terms[numTerms - 1]);
}
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);
}
// Testing basic funcionality of linguistic variables
private void runLingVarTestButton_Click(object sender, EventArgs e)
{
ClearDataSeries( );
// create a linguistic variable to represent temperature
LinguisticVariable lvTemperature = new LinguisticVariable("Temperature", 0, 80);
// create the linguistic labels (fuzzy sets) that compose the temperature
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);
// adding labels to the variable
lvTemperature.AddLabel(fsCold);
lvTemperature.AddLabel(fsCool);
lvTemperature.AddLabel(fsWarm);
lvTemperature.AddLabel(fsHot);
// get membership of some points to the cool fuzzy set
double[][,] chartValues = new double[4][, ];
for (int i = 0; i < 4; i++)
{
chartValues[i] = new double[160, 2];
}
// showing the shape of the linguistic variable - the shape of its labels memberships from start to end
int j = 0;
for (float x = 0; x < 80; x += 0.5f, j++)
{
double y1 = lvTemperature.GetLabelMembership("Cold", x);
double y2 = lvTemperature.GetLabelMembership("Cool", x);
double y3 = lvTemperature.GetLabelMembership("Warm", x);
double y4 = lvTemperature.GetLabelMembership("Hot", x);
chartValues[0][j, 0] = x;
chartValues[0][j, 1] = y1;
chartValues[1][j, 0] = x;
chartValues[1][j, 1] = y2;
chartValues[2][j, 0] = x;
chartValues[2][j, 1] = y3;
chartValues[3][j, 0] = x;
chartValues[3][j, 1] = y4;
}
// plot membership to a chart
chart.UpdateDataSeries("COLD", chartValues[0]);
chart.UpdateDataSeries("COOL", chartValues[1]);
chart.UpdateDataSeries("WARM", chartValues[2]);
chart.UpdateDataSeries("HOT", chartValues[3]);
}
private void SetSpeedFuzzySets()
{
fsSlow = new FuzzySet("Slow", new TrapezoidalFunction(30, 50, TrapezoidalFunction.EdgeType.Right));
fsMedium = new FuzzySet("Medium", new TrapezoidalFunction(30, 50, 80, 100));
fsFast = new FuzzySet("Fast", new TrapezoidalFunction(80, 100, TrapezoidalFunction.EdgeType.Left));
lvSpeed = new LinguisticVariable("Speed", 0, 100);
lvSpeed.AddLabel(fsSlow);
lvSpeed.AddLabel(fsMedium);
lvSpeed.AddLabel(fsFast);
}
private void SetDistanceFuzzySets()
{
fsNear = new FuzzySet("Near", new TrapezoidalFunction(20, 40, TrapezoidalFunction.EdgeType.Right));
fsMedi = new FuzzySet("Medi", new TrapezoidalFunction(20, 40, 50, 70));
fsFar = new FuzzySet("Far", new TrapezoidalFunction(50, 70, TrapezoidalFunction.EdgeType.Left));
lvDistance = new LinguisticVariable("Distance", 0, 100);
lvDistance.AddLabel(fsNear);
lvDistance.AddLabel(fsMedi);
lvDistance.AddLabel(fsFar);
}
private void SpeedFuzzySets()
{
fsSlow = new FuzzySet("Slow", new TrapezoidalFunction(5, 7, TrapezoidalFunction.EdgeType.Right));
fsMedium = new FuzzySet("Medium", new TrapezoidalFunction(5, 7, 10, 15));
fsFast = new FuzzySet("Fast", new TrapezoidalFunction(15, 20, TrapezoidalFunction.EdgeType.Left));
linSpeed = new LinguisticVariable("Speed", 0, 120);
linSpeed.AddLabel(fsSlow);
linSpeed.AddLabel(fsMedium);
linSpeed.AddLabel(fsFast);
}
private void DistanceFuzzySets()
{
fsNear = new FuzzySet("Near", new TrapezoidalFunction(0, 10, TrapezoidalFunction.EdgeType.Right));
fsMed = new FuzzySet("Med", new TrapezoidalFunction(0, 10, 15, 20));
fsFar = new FuzzySet("Far", new TrapezoidalFunction(20, 30, TrapezoidalFunction.EdgeType.Left));
linDistance = new LinguisticVariable("Distance", 0, 100);
linDistance.AddLabel(fsNear);
linDistance.AddLabel(fsMed);
linDistance.AddLabel(fsFar);
}
private void SetDistanceFuzzySets()
{
fsNear = new FuzzySet("Near", new TrapezoidalFunction(1, 3, TrapezoidalFunction.EdgeType.Right));
fsMed = new FuzzySet("Med", new TrapezoidalFunction(1, 3, 5, 7));
fsFar = new FuzzySet("Far", new TrapezoidalFunction(5, 7, TrapezoidalFunction.EdgeType.Left));
lvDistance = new LinguisticVariable("Distance", 0, 10);
lvDistance.AddLabel(fsNear);
lvDistance.AddLabel(fsMed);
lvDistance.AddLabel(fsFar);
}
private void SetDistanceFuzzySets()
{
Near = new FuzzySet("Near", new TrapezoidalFunction(5, 6, TrapezoidalFunction.EdgeType.Right));
Med = new FuzzySet("Med", new TrapezoidalFunction(6, 7, 8, 10));
Far = new FuzzySet("Far", new TrapezoidalFunction(13, 50, TrapezoidalFunction.EdgeType.Left));
lv_Distance = new LinguisticVariable("Distance", 0, 50);
lv_Distance.AddLabel(Near);
lv_Distance.AddLabel(Med);
lv_Distance.AddLabel(Far);
}
private void SetSpeedFuzzySets()
{
fsSlow = new FuzzySet("Slow", new TrapezoidalFunction(slowAC.keys[0].time, slowAC.keys[1].time, TrapezoidalFunction.EdgeType.Right));
fsMedium = new FuzzySet("Medium", new TrapezoidalFunction(mediumAC.keys[0].time, mediumAC.keys[1].time, mediumAC.keys[2].time, mediumAC.keys[3].time));
fsFast = new FuzzySet("Fast", new TrapezoidalFunction(fastAC.keys[0].time, fastAC.keys[1].time, TrapezoidalFunction.EdgeType.Left));
lvSpeed = new LinguisticVariable("Speed", 0, 120);
lvSpeed.AddLabel(fsSlow);
lvSpeed.AddLabel(fsMedium);
lvSpeed.AddLabel(fsFast);
}
private void SetSpeedFuzzySets()
{
Slow = new FuzzySet("Slow", new TrapezoidalFunction(4, 5, TrapezoidalFunction.EdgeType.Right));
Medium = new FuzzySet("Medium", new TrapezoidalFunction(4, 5, 8, 10));
Fast = new FuzzySet("Fast", new TrapezoidalFunction(8, 10, TrapezoidalFunction.EdgeType.Left));
lvSpeed = new LinguisticVariable("Speed", 0, 10);
lvSpeed.AddLabel(Slow);
lvSpeed.AddLabel(Medium);
lvSpeed.AddLabel(Fast);
}
private void SetDistanceFuzzySets()
{
fsNear = new FuzzySet("Near", new TrapezoidalFunction(nearAC.keys[0].time, nearAC.keys[1].time, TrapezoidalFunction.EdgeType.Right));
fsMed = new FuzzySet("Med", new TrapezoidalFunction(medAC.keys[0].time, medAC.keys[1].time, medAC.keys[2].time, medAC.keys[3].time));
fsFar = new FuzzySet("Far", new TrapezoidalFunction(farAC.keys[0].time, farAC.keys[1].time, TrapezoidalFunction.EdgeType.Left));
lvDistance = new LinguisticVariable("Distance", 0, 100);
lvDistance.AddLabel(fsNear);
lvDistance.AddLabel(fsMed);
lvDistance.AddLabel(fsFar);
}
private LinguisticVariable GetDistanceVariable()
{
FuzzySet distanceNear = new FuzzySet("Near", new TrapezoidalFunction(0, 0, 15, 22));
FuzzySet distanceFair = new FuzzySet("Fair", new TrapezoidalFunction(20, 30, 40));
LinguisticVariable lvDistance = new LinguisticVariable("Distance", 0, 40);
lvDistance.AddLabel(distanceNear);
lvDistance.AddLabel(distanceFair);
return(lvDistance);
}
public LinguisticVariable LinguistictDistance()
{
LinguisticVariable lDistance = new LinguisticVariable("Distance", 0, 500000);
FuzzySet fsFaible = new FuzzySet("Faible", new TrapezoidalFunction(30, 50, 500000, 0, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsMoyenne = new FuzzySet("Moyenne", new TrapezoidalFunction(40, 50, 100, 150));
FuzzySet fsGrande = new FuzzySet("Grande", new TrapezoidalFunction(100, 150, 500000, 0, TrapezoidalFunction.EdgeType.Left));
lDistance.AddLabel(fsFaible);
lDistance.AddLabel(fsMoyenne);
lDistance.AddLabel(fsGrande);
return(lDistance);
}
private LinguisticVariable LinguisticZoom()
{
LinguisticVariable lZ = new LinguisticVariable("Zoom", 1, 5);
FuzzySet fsPetit = new FuzzySet("Petit", new TrapezoidalFunction(1, 2, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsNormal = new FuzzySet("Normal", new TrapezoidalFunction(1, 2, 3, 4));
FuzzySet fsGros = new FuzzySet("Gros", new TrapezoidalFunction(3, 4, TrapezoidalFunction.EdgeType.Left));
lZ.AddLabel(fsPetit);
lZ.AddLabel(fsNormal);
lZ.AddLabel(fsGros);
return(lZ);
}
public LinguisticVariable LinguisticVitesse()
{
LinguisticVariable lV = new LinguisticVariable("Vitesse", 0, 200);
FuzzySet fsLente = new FuzzySet("Lente", new TrapezoidalFunction(20, 30, 200, 0, TrapezoidalFunction.EdgeType.Right));
FuzzySet fsPeuRapide = new FuzzySet("PeuRapide", new TrapezoidalFunction(20, 30, 70, 80));
FuzzySet fsRapide = new FuzzySet("Rapide", new TrapezoidalFunction(70, 80, 90, 110));
FuzzySet fsTresRapide = new FuzzySet("TresRapide", new TrapezoidalFunction(90, 110, 200, 0, TrapezoidalFunction.EdgeType.Left));
lV.AddLabel(fsLente);
lV.AddLabel(fsPeuRapide);
lV.AddLabel(fsRapide);
lV.AddLabel(fsTresRapide);
return(lV);
}
private LinguisticVariable GetDepthVariable(string depthType)
{
FuzzySet shallowDepth = new FuzzySet("Shallow", new TrapezoidalFunction(0, 2, 8, 10.5f));
FuzzySet fairlyDepth = new FuzzySet("Fairly", new TrapezoidalFunction(9.5f, 12, 18, 20.5f));
FuzzySet deepDepth = new FuzzySet("Deep", new TrapezoidalFunction(19.5f, 25, 35, 40.5f));
FuzzySet veryDeepDepth = new FuzzySet("VeryDeep", new TrapezoidalFunction(35, 40, float.MaxValue, float.MaxValue));
LinguisticVariable lvDepth = new LinguisticVariable(depthType, 0, float.MaxValue);
lvDepth.AddLabel(shallowDepth);
lvDepth.AddLabel(fairlyDepth);
lvDepth.AddLabel(deepDepth);
lvDepth.AddLabel(veryDeepDepth);
return(lvDepth);
}
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 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 LinguisticVariable GetSeismicityVariable(string seismicityType)
{
FuzzySet lowEnv = new FuzzySet("Low", new TrapezoidalFunction(1, 2.5f, 2.5f, 4.2f));
FuzzySet mediumEnv = new FuzzySet("Medium", new TrapezoidalFunction(3.8f, 4.5f, 4.5f, 5.2f));
FuzzySet strongEnv = new FuzzySet("Strong", new TrapezoidalFunction(4.8f, 6.5f, 6.5f, 9.2f));
FuzzySet greatEnv = new FuzzySet("Great", new TrapezoidalFunction(8.8f, 10.5f, 12, 12));
LinguisticVariable lvSeismicEnv = new LinguisticVariable(seismicityType, 1, 12);
lvSeismicEnv.AddLabel(lowEnv);
lvSeismicEnv.AddLabel(mediumEnv);
lvSeismicEnv.AddLabel(strongEnv);
lvSeismicEnv.AddLabel(greatEnv);
return(lvSeismicEnv);
}
private void Initialize()
{
_fVariable = new LinguisticVariable(Name, _range.Min, _range.Max);
foreach (FuzzySet label in _sets)
{
_fVariable.AddLabel(label);
}
_chartArea = _chart.ChartAreas[0];
_chartArea.AxisY.Maximum = 1;
_chartArea.AxisY.Minimum = 0;
_chartArea.AxisX.LabelStyle.Format = "{0}";
_chartArea.AxisX.LabelStyle.Interval = 2;
_chartArea.AxisY.LabelStyle.Format = "{0.0}";
_chartArea.AxisY.LabelStyle.Interval = 0.5;
//_chart = System.Windows.Forms.DockStyle.Bottom;
_chart.Legends.ToList().ForEach(x => x.Docking = Docking.Bottom);
if (Type == VariableType.Input)
{
InitialSelectLine();
}
}
/// <summary>
/// This is the method that actually does the work.
/// </summary>
/// <param name="DA">The DA object is used to retrieve from inputs and store in outputs.</param>
protected override void SolveInstance(IGH_DataAccess DA)
{
string Name = null;
Interval Interval = new Interval();
List <FuzzySet> fSets = new List <FuzzySet>();
if (!DA.GetData(0, ref Name))
{
return;
}
if (!DA.GetData(1, ref Interval))
{
return;
}
if (!DA.GetDataList(2, fSets))
{
return;
}
LinguisticVariable lingVar = new LinguisticVariable(Name, (float)Interval.Min, (float)Interval.Max);
foreach (object x in fSets)
{
FuzzySet func = (FuzzySet)x;
lingVar.AddLabel(func);
}
DA.SetData(0, lingVar);
}
public void SetFuzzyValues(float f1_1, float f2_1, float f1_X, float f2_X, float f3_X, float f4_X, float f1_2, float f2_2)
{
_lvlProbabilidad.ClearLabels();
_fsUno = new FuzzySet("UNO", new TrapezoidalFunction(f1_1, f2_1, TrapezoidalFunction.EdgeType.Left));
_fsEquis = new FuzzySet("EQUIS", new TrapezoidalFunction(f1_X, f2_X, f3_X, f4_X));
_fsDos = new FuzzySet("DOS", new TrapezoidalFunction(f1_2, f2_2, TrapezoidalFunction.EdgeType.Right));
Log.Info($"Setting Function for '2' with values 0 - {f1_2} - {f2_2}");
Log.Info($"Setting Function for 'X' with values {f1_X} - {f2_X} - {f3_X} - {f4_X}");
Log.Info($"Setting Function for '1' with values {f1_1} - {f2_1} - 100");
_lvlProbabilidad.AddLabel(_fsUno);
_lvlProbabilidad.AddLabel(_fsDos);
_lvlProbabilidad.AddLabel(_fsEquis);
IsSet = true;
}
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);
}
public static LinguisticVariable CreateVariable(string name, float start, float end, params FuzzySet[] labels)
{
LinguisticVariable lv = new LinguisticVariable(name, start, end);
for (int i = 0; i < labels.Length; i++)
{
lv.AddLabel(labels[i]);
}
return(lv);
}
private LinguisticVariable GetConcentrationVariable(string period, DateTime dateFrom, DateTime dateTo)
{
var offset = dateTo - dateFrom;
int days = offset.Days;
float bigPercent = 0.04f;
float mediumPercent = 0.02f;
float smallPercent = 0.01f;
FuzzySet smallConcentration = new FuzzySet("Small", new TrapezoidalFunction(0, 0, smallPercent * days, mediumPercent * days));
FuzzySet mediumConcentration = new FuzzySet("Medium", new TrapezoidalFunction(smallPercent * days, mediumPercent * days, bigPercent * days));
FuzzySet bigConcentration = new FuzzySet("Big", new TrapezoidalFunction(mediumPercent * days, bigPercent * days, TrapezoidalFunction.EdgeType.Left));
LinguisticVariable lvConcentration = new LinguisticVariable(period, 0, float.MaxValue);
lvConcentration.AddLabel(smallConcentration);
lvConcentration.AddLabel(mediumConcentration);
lvConcentration.AddLabel(bigConcentration);
return(lvConcentration);
}
private void SetLinguisticVariable() //ustawia zmienne lingwistyczne
{
airOutTemperature = new LinguisticVariable("AirOutTemperature", -20, 40);
airOutTemperature.AddLabel(tmpColdOut);
airOutTemperature.AddLabel(tmpHotOut);
airTemperature = new LinguisticVariable("AirTemperature", 0, 40);
airTemperature.AddLabel(tmpVeryCold);
airTemperature.AddLabel(tmpCold);
airTemperature.AddLabel(tmpMedium);
airTemperature.AddLabel(tmpHot);
airTemperature.AddLabel(tmpVeryHot);
Humidity = new LinguisticVariable("Humidity", 0, 100);
Humidity.AddLabel(smallHumidity);
Humidity.AddLabel(goodHumidity);
Humidity.AddLabel(bigHumidity);
HumidityOut = new LinguisticVariable("HumidityOut", 0, 100);
HumidityOut.AddLabel(smallHumidity);
HumidityOut.AddLabel(goodHumidity);
HumidityOut.AddLabel(bigHumidity);
desiredTemperature = new LinguisticVariable("DesiredTemperature", 0, 40);
desiredTemperature.AddLabel(tmpVeryCold);
desiredTemperature.AddLabel(tmpCold);
desiredTemperature.AddLabel(tmpMedium);
desiredTemperature.AddLabel(tmpHot);
desiredTemperature.AddLabel(tmpVeryHot);
FunTemperature = new LinguisticVariable("FunTemperature", 0, 40);
FunTemperature.AddLabel(tmpVeryCold);
FunTemperature.AddLabel(tmpCold);
FunTemperature.AddLabel(tmpMedium);
FunTemperature.AddLabel(tmpHot);
FunTemperature.AddLabel(tmpVeryHot);
FunStrenght = new LinguisticVariable("FunStrenght", 0, 100);
FunStrenght.AddLabel(veryLowStrenght);
FunStrenght.AddLabel(lowStrenght);
FunStrenght.AddLabel(mediumStrenght);
FunStrenght.AddLabel(hightStrenght);
FunStrenght.AddLabel(veryHightStrenght);
}
public LingVar(int number, string name, float min, float max, Scope[] scopes, int[] d)
{
this.min = min;
this.max = max;
range = Math.Abs(max - min);
terms = new FuzzySet[d.Length];
lv = new LinguisticVariable(name, min, max);
for (int i = 0; i < terms.Length; i++)
{
terms[i] = new FuzzySet(name + d[i].ToString(),
new TrapezoidalFunction(
(float)scopes[d[i]].min[number],
(float)scopes[d[i]].center[number],
(float)scopes[d[i]].max[number])
);
lv.AddLabel(terms[i]);
}
}
private LinguisticVariable GetMagnitudeVariable(string magType)
{
FuzzySet microMagnitude = new FuzzySet("Micro", new TrapezoidalFunction(0, 1, 1, 2.2f));
FuzzySet minorMagnitude = new FuzzySet("Minor", new TrapezoidalFunction(1.8f, 3, 3, 4.2f));
FuzzySet lightMagnitude = new FuzzySet("Light", new TrapezoidalFunction(3.8f, 4.5f, 4.5f, 5.2f));
FuzzySet moderateMagnitude = new FuzzySet("Moderate", new TrapezoidalFunction(4.8f, 5.5f, 5.5f, 6.2f));
FuzzySet strongMagnitude = new FuzzySet("Strong", new TrapezoidalFunction(5.8f, 6.5f, 6.5f, 7.2f));
FuzzySet majorMagnitude = new FuzzySet("Major", new TrapezoidalFunction(6.8f, 7.5f, 7.5f, 8.2f));
FuzzySet greatMagnitude = new FuzzySet("Great", new TrapezoidalFunction(7.8f, 8, 12, 12));
LinguisticVariable lvMagnitude = new LinguisticVariable(magType, 0, 12);
lvMagnitude.AddLabel(microMagnitude);
lvMagnitude.AddLabel(minorMagnitude);
lvMagnitude.AddLabel(lightMagnitude);
lvMagnitude.AddLabel(moderateMagnitude);
lvMagnitude.AddLabel(strongMagnitude);
lvMagnitude.AddLabel(majorMagnitude);
lvMagnitude.AddLabel(greatMagnitude);
return(lvMagnitude);
}
// 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");
}
