// Testing basic funcionality of fuzzy sets
private void runFuzzySetTestButton_Click( object sender, EventArgs e )
{
ClearDataSeries( );
// create 2 fuzzy sets to represent the Cool and Warm temperatures
TrapezoidalFunction function1 = new TrapezoidalFunction( 13, 18, 23, 28 );
FuzzySet fsCool = new FuzzySet( "Cool", function1 );
TrapezoidalFunction function2 = new TrapezoidalFunction( 23, 28, 33, 38 );
FuzzySet fsWarm = new FuzzySet( "Warm", function2 );
// get membership of some points to the cool fuzzy set
double[,] coolValues = new double[20, 2];
for ( int i = 10; i < 30; i++ )
{
coolValues[i - 10, 0] = i;
coolValues[i - 10, 1] = fsCool.GetMembership( i );
}
// getting memberships of some points to the warm fuzzy set
double[,] warmValues = new double[20, 2];
for ( int i = 20; i < 40; i++ )
{
warmValues[i - 20, 0] = i;
warmValues[i - 20, 1] = fsWarm.GetMembership( i );
}
// plot membership to a chart
chart.UpdateDataSeries( "COOL", coolValues );
chart.UpdateDataSeries( "WARM", warmValues );
}
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] );
}
public void SetInput2()
{
this.Power = new LinguisticVariable("Moc_samochodu", 20, 180);
TrapezoidalFunction function1 = new TrapezoidalFunction(40, 100, TrapezoidalFunction.EdgeType.Right);
FuzzySet set1 = new FuzzySet("mała", function1);
TrapezoidalFunction function2 = new TrapezoidalFunction(70, 100, 130);
FuzzySet set2 = new FuzzySet("średnia", function2);
TrapezoidalFunction function3 = new TrapezoidalFunction(100, 160, TrapezoidalFunction.EdgeType.Left);
FuzzySet set3 = new FuzzySet("duża", function3);
Power.AddLabel(set1);
Power.AddLabel(set2);
Power.AddLabel(set3);
database.AddVariable(Power);
double y1;
double y2;
double y3;
for (float x = 20; x < 180; x += 0.5f)
{
if (Power.GetLabelMembership("mała", x + 0.5f) + Power.GetLabelMembership("mała", x) > 0)
{
y1 = Power.GetLabelMembership("mała", x);
chart5.Series["Mała"].Points.AddXY(x, y1);
}
if (Power.GetLabelMembership("średnia", x + 0.5f) + Power.GetLabelMembership("średnia", x) > 0)
{
y2 = Power.GetLabelMembership("średnia", x);
chart5.Series["Średnia"].Points.AddXY(x, y2);
}
if (Power.GetLabelMembership("duża", x + 0.5f) + Power.GetLabelMembership("duża", x) > 0)
{
y3 = Power.GetLabelMembership("duża", x);
chart5.Series["Duża"].Points.AddXY(x, y3);
}
}
}
public void SetInput1()
{
this.Temp_opon = new LinguisticVariable("Temperatura", 0, 180);
TrapezoidalFunction function1 = new TrapezoidalFunction(30, 90, TrapezoidalFunction.EdgeType.Right);
FuzzySet set1 = new FuzzySet("zimne", function1);
TrapezoidalFunction function2 = new TrapezoidalFunction(70, 90, 110);
FuzzySet set2 = new FuzzySet("średnie", function2);
TrapezoidalFunction function3 = new TrapezoidalFunction(90, 150, TrapezoidalFunction.EdgeType.Left);
FuzzySet set3 = new FuzzySet("gorące", function3);
Temp_opon.AddLabel(set1);
Temp_opon.AddLabel(set2);
Temp_opon.AddLabel(set3);
database.AddVariable(Temp_opon);
double y1;
double y2;
double y3;
for (float x = 0; x < 180; x += 0.5f)
{
if (Temp_opon.GetLabelMembership("zimne", x + 0.5f) + Temp_opon.GetLabelMembership("zimne", x) > 0)
{
y1 = Temp_opon.GetLabelMembership("zimne", x);
chart4.Series["Zimne"].Points.AddXY(x, y1);
}
if (Temp_opon.GetLabelMembership("średnie", x + 0.5f) + Temp_opon.GetLabelMembership("średnie", x) > 0)
{
y2 = Temp_opon.GetLabelMembership("średnie", x);
chart4.Series["Średnie"].Points.AddXY(x, y2);
}
if (Temp_opon.GetLabelMembership("gorące", x + 0.5f) + Temp_opon.GetLabelMembership("gorące", x) > 0)
{
y3 = Temp_opon.GetLabelMembership("gorące", x);
chart4.Series["Gorące"].Points.AddXY(x, y3);
}
}
}
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 void SetOutput()
{
this.Risk = new LinguisticVariable("Ryzyko", 0, 30);
TrapezoidalFunction function1 = new TrapezoidalFunction(5, 10, TrapezoidalFunction.EdgeType.Right);
FuzzySet set1 = new FuzzySet("niskie", function1);
TrapezoidalFunction function2 = new TrapezoidalFunction(5, 10, 15);
FuzzySet set2 = new FuzzySet("średnio_niskie", function2);
TrapezoidalFunction function3 = new TrapezoidalFunction(10, 15, 20);
FuzzySet set3 = new FuzzySet("średnie", function3);
TrapezoidalFunction function4 = new TrapezoidalFunction(15, 20, 25);
FuzzySet set4 = new FuzzySet("średnio_wysokie", function4);
TrapezoidalFunction function5 = new TrapezoidalFunction(20, 25, TrapezoidalFunction.EdgeType.Left);
FuzzySet set5 = new FuzzySet("wysokie", function5);
Risk.AddLabel(set1);
Risk.AddLabel(set2);
Risk.AddLabel(set3);
Risk.AddLabel(set4);
Risk.AddLabel(set5);
database.AddVariable(Risk);
double y1;
double y2;
double y3;
double y4;
double y5;
for (float x = 0; x < 30; x += 0.05f)
{
if (Risk.GetLabelMembership("niskie", x + 0.05f) + Risk.GetLabelMembership("niskie", x) > 0)
{
y1 = Risk.GetLabelMembership("niskie", x);
chart6.Series["Niskie"].Points.AddXY(x, y1);
}
if (Risk.GetLabelMembership("średnio_niskie", x + 0.05f) + Risk.GetLabelMembership("średnio_niskie", x) > 0)
{
y2 = Risk.GetLabelMembership("średnio_niskie", x);
chart6.Series["Śr_nisk"].Points.AddXY(x, y2);
}
if (Risk.GetLabelMembership("średnie", x + 0.05f) + Risk.GetLabelMembership("średnie", x) > 0)
{
y3 = Risk.GetLabelMembership("średnie", x);
chart6.Series["Średnie"].Points.AddXY(x, y3);
}
if (Risk.GetLabelMembership("średnio_wysokie", x + 0.05f) + Risk.GetLabelMembership("średnio_wysokie", x) > 0)
{
y4 = Risk.GetLabelMembership("średnio_wysokie", x);
chart6.Series["Śr_wys"].Points.AddXY(x, y4);
}
if (Risk.GetLabelMembership("wysokie", x + 0.05f) + Risk.GetLabelMembership("wysokie", x) > 0)
{
y5 = Risk.GetLabelMembership("wysokie", x);
chart6.Series["Wysokie"].Points.AddXY(x, y5);
}
}
}
