MamdaniFuzzySystem CreateSystem()
{
//
// Create empty fuzzy system
//
MamdaniFuzzySystem fsTips = new MamdaniFuzzySystem();
//
// Create input variables for the system
//
FuzzyVariable fvService = new FuzzyVariable("service", 0.0, 10.0);
fvService.Terms.Add(new FuzzyTerm("poor", new TriangularMembershipFunction(-5.0, 0.0, 5.0)));
fvService.Terms.Add(new FuzzyTerm("good", new TriangularMembershipFunction(0.0, 5.0, 10.0)));
fvService.Terms.Add(new FuzzyTerm("excellent", new TriangularMembershipFunction(5.0, 10.0, 15.0)));
fsTips.Input.Add(fvService);
FuzzyVariable fvFood = new FuzzyVariable("food", 0.0, 10.0);
fvFood.Terms.Add(new FuzzyTerm("rancid", new TrapezoidMembershipFunction(0.0, 0.0, 1.0, 3.0)));
fvFood.Terms.Add(new FuzzyTerm("delicious", new TrapezoidMembershipFunction(7.0, 9.0, 10.0, 10.0)));
fsTips.Input.Add(fvFood);
//
// Create output variables for the system
//
FuzzyVariable fvTips = new FuzzyVariable("tips", 0.0, 30.0);
fvTips.Terms.Add(new FuzzyTerm("cheap", new TriangularMembershipFunction(0.0, 5.0, 10.0)));
fvTips.Terms.Add(new FuzzyTerm("average", new TriangularMembershipFunction(10.0, 15.0, 20.0)));
fvTips.Terms.Add(new FuzzyTerm("generous", new TriangularMembershipFunction(20.0, 25.0, 30.0)));
fsTips.Output.Add(fvTips);
//
// Create three fuzzy rules
//
try
{
MamdaniFuzzyRule rule1 = fsTips.ParseRule("if (service is poor ) or (food is rancid) then tips is cheap");
MamdaniFuzzyRule rule2 = fsTips.ParseRule("if ((service is good)) then tips is average");
MamdaniFuzzyRule rule3 = fsTips.ParseRule("if (service is excellent) or (food is delicious) then (tips is generous)");
fsTips.Rules.Add(rule1);
fsTips.Rules.Add(rule2);
fsTips.Rules.Add(rule3);
}
catch (Exception ex)
{
MessageBox.Show(string.Format("Parsing exception: {0}", ex.Message));
return(null);
}
return(fsTips);
}
public HouseMemberFuzzyCalc([NotNull] Logging.Logger logger)
{
_logger = logger;
//
// Create empty fuzzy system
//
//
// Create input variables for the system
//
var energy = new FuzzyVariable("energy", 0.0, 10000.0);
//// finetune these parameters some more / automate the fine tuning
energy.Terms.Add(new FuzzyTerm("zeroenergy", new TriangularMembershipFunction(-5.0, 0.0, 1000)));
energy.Terms.Add(new FuzzyTerm("onethousand", new TrapezoidMembershipFunction(1000, 1200, 1300, 1800)));
energy.Terms.Add(new FuzzyTerm("twothousand", new TrapezoidMembershipFunction(1500, 2200, 2500, 3500)));
energy.Terms.Add(new FuzzyTerm("threethousand", new TrapezoidMembershipFunction(3300, 4000, 4700, 5000)));
energy.Terms.Add(new FuzzyTerm("fourthousand", new TrapezoidMembershipFunction(4500, 5000, 6000, 6500)));
energy.Terms.Add(new FuzzyTerm("fivethousand", new TriangularMembershipFunction(6500, 7500, 8000)));
energy.Terms.Add(new FuzzyTerm("sixthousand", new TriangularMembershipFunction(7000, 8000, 10000)));
_fsTips.Input.Add(energy);
/*FuzzyVariable fvFood = new FuzzyVariable("food", 0.0, 10.0);
* fvFood.Terms.Add(new FuzzyTerm("rancid", new TrapezoidMembershipFunction(0.0, 0.0, 1.0, 3.0)));
* fvFood.Terms.Add(new FuzzyTerm("delicious", new TrapezoidMembershipFunction(7.0, 9.0, 10.0, 10.0)));
* fsTips.Input.Add(fvFood);*/
//
// Create output variables for the system
//
var people = new FuzzyVariable("people", 0.0, 10);
people.Terms.Add(new FuzzyTerm("zero", new TriangularMembershipFunction(0.0, 0.2, 0.5)));
people.Terms.Add(new FuzzyTerm("oneperson", new TriangularMembershipFunction(0.0, 1, 2)));
people.Terms.Add(new FuzzyTerm("twopersons", new TriangularMembershipFunction(1, 2, 3)));
people.Terms.Add(new FuzzyTerm("threepersons", new TriangularMembershipFunction(2, 3, 4)));
people.Terms.Add(new FuzzyTerm("fourpersons", new TriangularMembershipFunction(3, 4, 5)));
people.Terms.Add(new FuzzyTerm("fivepersons", new TriangularMembershipFunction(4, 5, 6)));
people.Terms.Add(new FuzzyTerm("sixpersons", new TriangularMembershipFunction(5, 6, 7)));
_fsTips.Output.Add(people);
//
// Create three fuzzy rules
//
// try
// {// or (food is rancid)
_fsTips.Rules.Add(_fsTips.ParseRule("if (energy is zeroenergy ) then people is zero"));
_fsTips.Rules.Add(_fsTips.ParseRule("if (energy is onethousand) then people is oneperson"));
_fsTips.Rules.Add(_fsTips.ParseRule("if (energy is twothousand) then (people is twopersons)"));
_fsTips.Rules.Add(_fsTips.ParseRule("if (energy is threethousand) then (people is threepersons)"));
_fsTips.Rules.Add(_fsTips.ParseRule("if (energy is fourthousand) then (people is fourpersons)"));
_fsTips.Rules.Add(_fsTips.ParseRule("if (energy is fivethousand) then (people is fivepersons)"));
_fsTips.Rules.Add(_fsTips.ParseRule("if (energy is sixthousand) then (people is sixpersons)"));
}
void AddFuzzyRule(string rule)
{
fuzzyEngine.Rules.Add(fuzzyEngine.ParseRule(rule));
}
public static Dictionary <NodeInstance, double> PrioritizeNodes(List <NodeInstance> nodes)
{
MamdaniFuzzySystem fsNodeSys = new MamdaniFuzzySystem();
FuzzyVariable fvCPU = new FuzzyVariable("cpu", 0.0, 1);
fvCPU.Terms.Add(new FuzzyTerm("low", new TriangularMembershipFunction(-.50, 0, .50)));
fvCPU.Terms.Add(new FuzzyTerm("med", new TriangularMembershipFunction(0, .50, 1)));
fvCPU.Terms.Add(new FuzzyTerm("high", new TriangularMembershipFunction(.50, 1, 1.5)));
fsNodeSys.Input.Add(fvCPU);
FuzzyVariable fvBandwidth = new FuzzyVariable("bandwidth", 0.0, 1);
fvBandwidth.Terms.Add(new FuzzyTerm("low", new TriangularMembershipFunction(-.50, 0, .50)));
fvBandwidth.Terms.Add(new FuzzyTerm("med", new TriangularMembershipFunction(0, .50, 1)));
fvBandwidth.Terms.Add(new FuzzyTerm("high", new TriangularMembershipFunction(.50, 1, 1.5)));
fsNodeSys.Input.Add(fvBandwidth);
FuzzyVariable fvFreeSpace = new FuzzyVariable("freespace", 0.0, 1);
fvFreeSpace.Terms.Add(new FuzzyTerm("low", new TriangularMembershipFunction(-.5, 0, .5)));
fvFreeSpace.Terms.Add(new FuzzyTerm("moderate", new TriangularMembershipFunction(0, .5, 1)));
fvFreeSpace.Terms.Add(new FuzzyTerm("ample", new TriangularMembershipFunction(.5, 1, 1.5)));
fsNodeSys.Input.Add(fvFreeSpace);
//
// Create output variables for the system
//
FuzzyVariable fvRank = new FuzzyVariable("rank", 0, 1);
fvRank.Terms.Add(new FuzzyTerm("low", new TriangularMembershipFunction(-0.25, 0, 0.25)));
fvRank.Terms.Add(new FuzzyTerm("med_low", new TriangularMembershipFunction(0, 0.25, 0.50)));
fvRank.Terms.Add(new FuzzyTerm("med", new TriangularMembershipFunction(0.25, 0.50, 0.75)));
fvRank.Terms.Add(new FuzzyTerm("med_high", new TriangularMembershipFunction(0.50, 0.75, 1)));
fvRank.Terms.Add(new FuzzyTerm("high", new TriangularMembershipFunction(0.75, 1, 1.25)));
fsNodeSys.Output.Add(fvRank);
MamdaniFuzzyRule rule1 = fsNodeSys.ParseRule("if (cpu is low) and (bandwidth is high) and (freespace is ample) then rank is med");
MamdaniFuzzyRule rule2 = fsNodeSys.ParseRule("if (cpu is low) and (bandwidth is high) and (freespace is moderate) then rank is med_low");
MamdaniFuzzyRule rule3 = fsNodeSys.ParseRule("if (cpu is low) and (bandwidth is high) and (freespace is low) then rank is low");
MamdaniFuzzyRule rule4 = fsNodeSys.ParseRule("if (cpu is low) and (bandwidth is med) and (freespace is ample) then rank is med_high");
MamdaniFuzzyRule rule5 = fsNodeSys.ParseRule("if (cpu is low) and (bandwidth is med) and (freespace is moderate) then rank is med_high");
MamdaniFuzzyRule rule6 = fsNodeSys.ParseRule("if (cpu is low) and (bandwidth is med) and (freespace is low) then rank is med_low");
MamdaniFuzzyRule rule7 = fsNodeSys.ParseRule("if (cpu is low) and (bandwidth is low) and (freespace is ample) then rank is high");
MamdaniFuzzyRule rule8 = fsNodeSys.ParseRule("if (cpu is low) and (bandwidth is low) and (freespace is moderate) then rank is med_high");
MamdaniFuzzyRule rule9 = fsNodeSys.ParseRule("if (cpu is low) and (bandwidth is low) and (freespace is low) then rank is med_low");
MamdaniFuzzyRule rule10 = fsNodeSys.ParseRule("if (cpu is med) and (bandwidth is high) and (freespace is ample) then rank is med");
MamdaniFuzzyRule rule11 = fsNodeSys.ParseRule("if (cpu is med) and (bandwidth is high) and (freespace is moderate) then rank is med_low");
MamdaniFuzzyRule rule12 = fsNodeSys.ParseRule("if (cpu is med) and (bandwidth is high) and (freespace is low) then rank is med_low");
MamdaniFuzzyRule rule13 = fsNodeSys.ParseRule("if (cpu is med) and (bandwidth is med) and (freespace is ample) then rank is med");
MamdaniFuzzyRule rule14 = fsNodeSys.ParseRule("if (cpu is med) and (bandwidth is med) and (freespace is moderate) then rank is med");
MamdaniFuzzyRule rule15 = fsNodeSys.ParseRule("if (cpu is med) and (bandwidth is med) and (freespace is low) then rank is low");
MamdaniFuzzyRule rule16 = fsNodeSys.ParseRule("if (cpu is med) and (bandwidth is low) and (freespace is ample) then rank is med_high");
MamdaniFuzzyRule rule17 = fsNodeSys.ParseRule("if (cpu is med) and (bandwidth is low) and (freespace is moderate) then rank is med_high");
MamdaniFuzzyRule rule18 = fsNodeSys.ParseRule("if (cpu is med) and (bandwidth is low) and (freespace is low) then rank is low");
MamdaniFuzzyRule rule19 = fsNodeSys.ParseRule("if (cpu is high) and (bandwidth is high) and (freespace is ample) then rank is med");
MamdaniFuzzyRule rule20 = fsNodeSys.ParseRule("if (cpu is high) and (bandwidth is high) and (freespace is moderate) then rank is med_low");
MamdaniFuzzyRule rule21 = fsNodeSys.ParseRule("if (cpu is high) and (bandwidth is high) and (freespace is low) then rank is low");
MamdaniFuzzyRule rule22 = fsNodeSys.ParseRule("if (cpu is high) and (bandwidth is med) and (freespace is ample) then rank is med");
MamdaniFuzzyRule rule23 = fsNodeSys.ParseRule("if (cpu is high) and (bandwidth is med) and (freespace is moderate) then rank is med_low");
MamdaniFuzzyRule rule24 = fsNodeSys.ParseRule("if (cpu is high) and (bandwidth is med) and (freespace is low) then rank is low");
MamdaniFuzzyRule rule25 = fsNodeSys.ParseRule("if (cpu is high) and (bandwidth is low) and (freespace is ample) then rank is med_low");
MamdaniFuzzyRule rule26 = fsNodeSys.ParseRule("if (cpu is high) and (bandwidth is low) and (freespace is moderate) then rank is med");
MamdaniFuzzyRule rule27 = fsNodeSys.ParseRule("if (cpu is high) and (bandwidth is low) and (freespace is low) then rank is low");
fsNodeSys.Rules.Add(rule1);
fsNodeSys.Rules.Add(rule2);
fsNodeSys.Rules.Add(rule3);
fsNodeSys.Rules.Add(rule4);
fsNodeSys.Rules.Add(rule5);
fsNodeSys.Rules.Add(rule6);
fsNodeSys.Rules.Add(rule7);
fsNodeSys.Rules.Add(rule8);
fsNodeSys.Rules.Add(rule9);
fsNodeSys.Rules.Add(rule10);
fsNodeSys.Rules.Add(rule11);
fsNodeSys.Rules.Add(rule12);
fsNodeSys.Rules.Add(rule13);
fsNodeSys.Rules.Add(rule14);
fsNodeSys.Rules.Add(rule15);
fsNodeSys.Rules.Add(rule16);
fsNodeSys.Rules.Add(rule17);
fsNodeSys.Rules.Add(rule18);
fsNodeSys.Rules.Add(rule19);
fsNodeSys.Rules.Add(rule20);
fsNodeSys.Rules.Add(rule21);
fsNodeSys.Rules.Add(rule22);
fsNodeSys.Rules.Add(rule23);
fsNodeSys.Rules.Add(rule24);
fsNodeSys.Rules.Add(rule25);
fsNodeSys.Rules.Add(rule26);
fsNodeSys.Rules.Add(rule27);
var rankedNodes = new Dictionary <NodeInstance, double>();
for (int i = 0; i < nodes.Count; i++)
{
//
// Fuzzify input values
//
Dictionary <FuzzyVariable, double> inputValues = new Dictionary <FuzzyVariable, double>();
inputValues.Add(fvCPU, nodes[i].CPU_Utilization);
inputValues.Add(fvBandwidth, nodes[i].UsedBandwidth / nodes[i].MaxBandwidth);
inputValues.Add(fvFreeSpace, nodes[i].FreeSpace / nodes[i].MaxBackupSpace);
//
// Calculate the result
//
Dictionary <FuzzyVariable, double> result = fsNodeSys.Calculate(inputValues);
double rank = result[fvRank];
rankedNodes.Add(nodes[i], rank);
//Console.WriteLine(nodes[i].ToString());
//Console.WriteLine("Rank: " + Math.Round(rank, 2).ToString());
//Console.WriteLine();
}
var sortedNodes
= (from entry in rankedNodes orderby entry.Value descending select entry)
.ToDictionary(pair => pair.Key, pair => pair.Value);
return(sortedNodes);
}
private FuzzySystemResultDTO GenerateSystem(GetRuleDTO rules, double inputValue)
{
FuzzySystemResultDTO result = new FuzzySystemResultDTO();
MamdaniFuzzySystem fsSoil = new MamdaniFuzzySystem();
foreach (var variable in rules.VariableList)
{
if (variable.DegiskenTipID == (byte)Enums.VariableType.Input)
{
FuzzyVariable fvInput = new FuzzyVariable(variable.DegiskenGorunenAdi, 0.0, 1000.0);
var variableItems = rules.VariableItemList.Where(k => k.DegiskenID == variable.DegiskenID).ToList();
for (int i = 0; i < variableItems.Count; i++)
{
if (inputValue == variableItems[i].MinDeger)
{
inputValue++;
}
double maxValue;
if (i != variableItems.Count - 1)
{
if (variableItems[i].MaxDeger == variableItems[i + 1].MinDeger)
{
maxValue = variableItems[i].MaxDeger - 1;
}
else
{
maxValue = variableItems[i].MaxDeger;
}
}
else
{
maxValue = variableItems[i].MaxDeger;
}
fvInput.Terms.Add(new FuzzyTerm(variableItems[i].DegiskenItemGorunenAdi, new TriangularMembershipFunction(variableItems[i].MinDeger, (variableItems[i].MinDeger + variableItems[i].MaxDeger) / 2, maxValue)));
}
fsSoil.Input.Add(fvInput);
}
else
{
FuzzyVariable fvOutput = new FuzzyVariable(variable.DegiskenGorunenAdi, 0.0, 1000.0);
var variableItems = rules.VariableItemList.Where(k => k.DegiskenID == variable.DegiskenID).ToList();
for (int i = 0; i < variableItems.Count; i++)
{
double maxValue;
if (i != variableItems.Count - 1)
{
if (variableItems[i].MaxDeger == variableItems[i + 1].MinDeger)
{
maxValue = variableItems[i].MaxDeger - 1;
}
else
{
maxValue = variableItems[i].MaxDeger;
}
}
else
{
maxValue = variableItems[i].MaxDeger;
}
fvOutput.Terms.Add(new FuzzyTerm(variableItems[i].DegiskenItemGorunenAdi, new TriangularMembershipFunction(variableItems[i].MinDeger, (variableItems[i].MinDeger + variableItems[i].MaxDeger) / 2, maxValue)));
}
fsSoil.Output.Add(fvOutput);
}
}
foreach (var ruleText in rules.RuleListText)
{
MamdaniFuzzyRule rule = fsSoil.ParseRule(ruleText.KuralText);
fsSoil.Rules.Add(rule);
}
result.System = fsSoil;
result.InputValue = inputValue;
return(result);
}
private FuzzySystemResultDTO CreateSystem(FetchRuleDTO rules, double inputValue)
{
FuzzySystemResultDTO result = new FuzzySystemResultDTO();
MamdaniFuzzySystem fsGround = new MamdaniFuzzySystem();
rules.VariableList = session.variables;
rules.RuleListText = session.rules;
rules.VariableItemList = session.variableItems;
foreach (var variable in rules.VariableList)
{
if (variable.variableTypeID == (byte)Enums.VariableType.Input)
{
FuzzyVariable fvInput = new FuzzyVariable(variable.visibleVariableName, 0.0, 1000.0);
var variableItems = rules.VariableItemList.Where(k => k.variableID == variable.variableID).ToList();
for (int i = 0; i < variableItems.Count; i++)
{
if (inputValue == variableItems[i].minValue)
{
inputValue++;
}
double maxValue;
if (i != variableItems.Count - 1)
{
if (variableItems[i].maxValue == variableItems[i + 1].minValue)
{
maxValue = variableItems[i].maxValue - 1;
}
else
{
maxValue = variableItems[i].maxValue;
}
}
else
{
maxValue = variableItems[i].maxValue;
}
fvInput.Terms.Add(new FuzzyTerm(variableItems[i].variableItemVisibleName, new TriangularMembershipFunction(variableItems[i].minValue, (variableItems[i].minValue + variableItems[i].maxValue) / 2, maxValue)));
}
fsGround.Input.Add(fvInput);
}
else
{
FuzzyVariable fvOutput = new FuzzyVariable(variable.visibleVariableName, 0.0, 1000.0);
var variableItems = rules.VariableItemList.Where(k => k.variableID == variable.variableID).ToList();
for (int i = 0; i < variableItems.Count; i++)
{
double maxValue;
if (i != variableItems.Count - 1)
{
if (variableItems[i].maxValue == variableItems[i + 1].minValue)
{
maxValue = variableItems[i].maxValue - 1;
}
else
{
maxValue = variableItems[i].maxValue;
}
}
else
{
maxValue = variableItems[i].maxValue;
}
fvOutput.Terms.Add(new FuzzyTerm(variableItems[i].variableItemVisibleName, new TriangularMembershipFunction(variableItems[i].minValue, (variableItems[i].minValue + variableItems[i].maxValue) / 2, maxValue)));
}
fsGround.Output.Add(fvOutput);
}
}
foreach (var ruleText in rules.RuleListText)
{
MamdaniFuzzyRule rule = fsGround.ParseRule(ruleText.ruleText);
fsGround.Rules.Add(rule);
}
result.System = fsGround;
result.InputValue = inputValue;
return(result);
}
MamdaniFuzzySystem CrearSistemaCostoCalidad()
{
MamdaniFuzzySystem fsCostoCalidad = new MamdaniFuzzySystem();
FuzzyVariable fvCalidadProducto = new FuzzyVariable("calidad_producto", 0.0, 1.0);
fvCalidadProducto.Terms.Add(new FuzzyTerm("muy_mala", new TrapezoidMembershipFunction(0.0, 0.0, 0.1, 0.3)));
fvCalidadProducto.Terms.Add(new FuzzyTerm("mala", new TriangularMembershipFunction(0.1, 0.3, 0.5)));
fvCalidadProducto.Terms.Add(new FuzzyTerm("regular", new TriangularMembershipFunction(0.3, 0.5, 0.7)));
fvCalidadProducto.Terms.Add(new FuzzyTerm("buena", new TriangularMembershipFunction(0.5, 0.7, 0.9)));
fvCalidadProducto.Terms.Add(new FuzzyTerm("excelente", new TrapezoidMembershipFunction(0.7, 0.9, 1.0, 1.0)));
fsCostoCalidad.Input.Add(fvCalidadProducto);
FuzzyVariable fvCostoTotal = new FuzzyVariable("costo_total", 0.0, 1.0);
fvCostoTotal.Terms.Add(new FuzzyTerm("no_tiene", new TrapezoidMembershipFunction(0.0, 0.0, 0.1, 0.3)));
fvCostoTotal.Terms.Add(new FuzzyTerm("bajo", new TriangularMembershipFunction(0.1, 0.3, 0.5)));
fvCostoTotal.Terms.Add(new FuzzyTerm("regular", new TriangularMembershipFunction(0.3, 0.5, 0.7)));
fvCostoTotal.Terms.Add(new FuzzyTerm("alto", new TriangularMembershipFunction(0.5, 0.7, 0.9)));
fvCostoTotal.Terms.Add(new FuzzyTerm("muy_alto", new TrapezoidMembershipFunction(0.7, 0.9, 1.0, 1.0)));
fsCostoCalidad.Input.Add(fvCostoTotal);
FuzzyVariable fvPuntajeSoftware = new FuzzyVariable("puntaje_software", 0.0, 1.0);
fvPuntajeSoftware.Terms.Add(new FuzzyTerm("muy_malo", new TrapezoidMembershipFunction(0.0, 0.0, 0.1, 0.3)));
fvPuntajeSoftware.Terms.Add(new FuzzyTerm("malo", new TriangularMembershipFunction(0.1, 0.3, 0.5)));
fvPuntajeSoftware.Terms.Add(new FuzzyTerm("regular", new TriangularMembershipFunction(0.3, 0.5, 0.7)));
fvPuntajeSoftware.Terms.Add(new FuzzyTerm("bueno", new TriangularMembershipFunction(0.5, 0.7, 0.9)));
fvPuntajeSoftware.Terms.Add(new FuzzyTerm("excelente", new TrapezoidMembershipFunction(0.7, 0.9, 1.0, 1.0)));
fsCostoCalidad.Output.Add(fvPuntajeSoftware);
try
{
MamdaniFuzzyRule r0 = fsCostoCalidad.ParseRule("if (calidad_producto is muy_mala) and (costo_total is no_tiene) then puntaje_software is muy_malo");
MamdaniFuzzyRule r1 = fsCostoCalidad.ParseRule("if (calidad_producto is mala) and (costo_total is no_tiene) then puntaje_software is malo");
MamdaniFuzzyRule r2 = fsCostoCalidad.ParseRule("if (calidad_producto is regular) and (costo_total is no_tiene) then puntaje_software is regular");
MamdaniFuzzyRule r3 = fsCostoCalidad.ParseRule("if (calidad_producto is buena) and (costo_total is no_tiene) then puntaje_software is bueno");
MamdaniFuzzyRule r4 = fsCostoCalidad.ParseRule("if (calidad_producto is excelente) and (costo_total is no_tiene) then puntaje_software is excelente");
MamdaniFuzzyRule r5 = fsCostoCalidad.ParseRule("if (calidad_producto is muy_mala) and (costo_total is bajo) then puntaje_software is muy_malo");
MamdaniFuzzyRule r6 = fsCostoCalidad.ParseRule("if (calidad_producto is mala) and (costo_total is bajo) then puntaje_software is malo");
MamdaniFuzzyRule r7 = fsCostoCalidad.ParseRule("if (calidad_producto is regular) and (costo_total is bajo) then puntaje_software is regular");
MamdaniFuzzyRule r8 = fsCostoCalidad.ParseRule("if (calidad_producto is buena) and (costo_total is bajo) then puntaje_software is bueno");
MamdaniFuzzyRule r9 = fsCostoCalidad.ParseRule("if (calidad_producto is excelente) and (costo_total is bajo) then puntaje_software is excelente");
MamdaniFuzzyRule r10 = fsCostoCalidad.ParseRule("if (calidad_producto is muy_mala) and (costo_total is regular) then puntaje_software is muy_malo");
MamdaniFuzzyRule r11 = fsCostoCalidad.ParseRule("if (calidad_producto is mala) and (costo_total is regular) then puntaje_software is muy_malo");
MamdaniFuzzyRule r12 = fsCostoCalidad.ParseRule("if (calidad_producto is regular) and (costo_total is regular) then puntaje_software is regular");
MamdaniFuzzyRule r13 = fsCostoCalidad.ParseRule("if (calidad_producto is buena) and (costo_total is regular) then puntaje_software is regular");
MamdaniFuzzyRule r14 = fsCostoCalidad.ParseRule("if (calidad_producto is excelente) and (costo_total is regular) then puntaje_software is bueno");
MamdaniFuzzyRule r15 = fsCostoCalidad.ParseRule("if (calidad_producto is muy_mala) and (costo_total is alto) then puntaje_software is muy_malo");
MamdaniFuzzyRule r16 = fsCostoCalidad.ParseRule("if (calidad_producto is mala) and (costo_total is alto) then puntaje_software is muy_malo");
MamdaniFuzzyRule r17 = fsCostoCalidad.ParseRule("if (calidad_producto is regular) and (costo_total is alto) then puntaje_software is malo");
MamdaniFuzzyRule r18 = fsCostoCalidad.ParseRule("if (calidad_producto is buena) and (costo_total is alto) then puntaje_software is regular");
MamdaniFuzzyRule r19 = fsCostoCalidad.ParseRule("if (calidad_producto is excelente) and (costo_total is alto) then puntaje_software is regular");
MamdaniFuzzyRule r20 = fsCostoCalidad.ParseRule("if (calidad_producto is muy_mala) and (costo_total is muy_alto) then puntaje_software is muy_malo");
MamdaniFuzzyRule r21 = fsCostoCalidad.ParseRule("if (calidad_producto is mala) and (costo_total is muy_alto) then puntaje_software is muy_malo");
MamdaniFuzzyRule r22 = fsCostoCalidad.ParseRule("if (calidad_producto is regular) and (costo_total is muy_alto) then puntaje_software is malo");
MamdaniFuzzyRule r23 = fsCostoCalidad.ParseRule("if (calidad_producto is buena) and (costo_total is muy_alto) then puntaje_software is malo");
MamdaniFuzzyRule r24 = fsCostoCalidad.ParseRule("if (calidad_producto is excelente) and (costo_total is muy_alto) then puntaje_software is regular");
fsCostoCalidad.Rules.Add(r0);
fsCostoCalidad.Rules.Add(r1);
fsCostoCalidad.Rules.Add(r2);
fsCostoCalidad.Rules.Add(r3);
fsCostoCalidad.Rules.Add(r4);
fsCostoCalidad.Rules.Add(r5);
fsCostoCalidad.Rules.Add(r6);
fsCostoCalidad.Rules.Add(r7);
fsCostoCalidad.Rules.Add(r8);
fsCostoCalidad.Rules.Add(r9);
fsCostoCalidad.Rules.Add(r10);
fsCostoCalidad.Rules.Add(r11);
fsCostoCalidad.Rules.Add(r12);
fsCostoCalidad.Rules.Add(r13);
fsCostoCalidad.Rules.Add(r14);
fsCostoCalidad.Rules.Add(r15);
fsCostoCalidad.Rules.Add(r16);
fsCostoCalidad.Rules.Add(r17);
fsCostoCalidad.Rules.Add(r18);
fsCostoCalidad.Rules.Add(r19);
fsCostoCalidad.Rules.Add(r20);
fsCostoCalidad.Rules.Add(r21);
fsCostoCalidad.Rules.Add(r22);
fsCostoCalidad.Rules.Add(r23);
fsCostoCalidad.Rules.Add(r24);
}
catch (Exception ex)
{
Console.WriteLine(string.Format("Parsing exception: {0}", ex.Message));
//MessageBox.Show(string.Format("Parsing exception: {0}", ex.Message));
return(null);
}
return(fsCostoCalidad);
}
protected virtual void AddingRulesForNormalOwnHealth()
{
//1 OwnHealth is Normal
fuzzyEngine.Rules.Add(fuzzyEngine.ParseRule("if ((OwnHealth is Normal) " +
"and ((EnemyHealth is NearDead) or (EnemyHealth is Injured) or (EnemyHealth is Normal)) " +
"and ((RelativeAttackPower is Weak) or (RelativeAttackPower is Equal) or (RelativeAttackPower is Strong)) " +
"and ((RelativeSpeed is Slow) or (RelativeSpeed is Equal) or (RelativeSpeed is Fast))) " +
"then AttackOrFlee is Attack"));
}
void initAstronaut()
{
_fsAstronaut = new MamdaniFuzzySystem();
fvHunger = new FuzzyVariable("Hunger", 0.0, 1.0);
fvHunger.Terms.Add(new FuzzyTerm("minimal", new TrapezoidMembershipFunction(0.0, 0.0, 0.2, 0.2)));
fvHunger.Terms.Add(new FuzzyTerm("low", new TriangularMembershipFunction(0.0, 0.3, 0.5)));
fvHunger.Terms.Add(new FuzzyTerm("normal", new TriangularMembershipFunction(0.2, 0.5, 0.8)));
fvHunger.Terms.Add(new FuzzyTerm("high", new TriangularMembershipFunction(0.5, 0.7, 1.0)));
fvHunger.Terms.Add(new FuzzyTerm("maximal", new TrapezoidMembershipFunction(0.8, 0.8, 1.0, 1.0)));
_fsAstronaut.Input.Add(fvHunger);
fvThirst = new FuzzyVariable("Thirst", 0.0, 1.0);
fvThirst.Terms.Add(new FuzzyTerm("minimal", new TrapezoidMembershipFunction(0.0, 0.0, 0.2, 0.2)));
fvThirst.Terms.Add(new FuzzyTerm("low", new TriangularMembershipFunction(0.0, 0.3, 0.5)));
fvThirst.Terms.Add(new FuzzyTerm("normal", new TriangularMembershipFunction(0.2, 0.5, 0.8)));
fvThirst.Terms.Add(new FuzzyTerm("high", new TriangularMembershipFunction(0.5, 0.7, 1.0)));
fvThirst.Terms.Add(new FuzzyTerm("maximal", new TrapezoidMembershipFunction(0.8, 0.8, 1.0, 1.0)));
_fsAstronaut.Input.Add(fvThirst);
fvTiredness = new FuzzyVariable("Tiredness", 0.0, 1.0);
fvTiredness.Terms.Add(new FuzzyTerm("minimal", new TrapezoidMembershipFunction(0.0, 0.0, 0.2, 0.2)));
fvTiredness.Terms.Add(new FuzzyTerm("low", new TriangularMembershipFunction(0.0, 0.3, 0.5)));
fvTiredness.Terms.Add(new FuzzyTerm("normal", new TriangularMembershipFunction(0.2, 0.5, 0.8)));
fvTiredness.Terms.Add(new FuzzyTerm("high", new TriangularMembershipFunction(0.5, 0.7, 1.0)));
fvTiredness.Terms.Add(new FuzzyTerm("maximal", new TrapezoidMembershipFunction(0.8, 0.8, 1.0, 1.0)));
_fsAstronaut.Input.Add(fvTiredness);
FuzzyVariable svTarget = new FuzzyVariable("Target", 0, 1.0);
svTarget.Terms.Add(new FuzzyTerm("sleep", new TrapezoidMembershipFunction(0.0, 0.0, 0.3, 0.6)));
svTarget.Terms.Add(new FuzzyTerm("eat", new TrapezoidMembershipFunction(0.3, 0.5, 0.6, 0.7)));
svTarget.Terms.Add(new FuzzyTerm("work", new TrapezoidMembershipFunction(0.6, 0.6, 1.0, 1.0)));
_fsAstronaut.Output.Add(svTarget);
MamdaniFuzzyRule rule1 = _fsAstronaut.ParseRule("if (Hunger is high) or (Thirst is high) or (Hunger is maximal) or (Thirst is maximal) then (Target is eat)");
MamdaniFuzzyRule rule2 = _fsAstronaut.ParseRule("if (Tiredness is normal) or(Tiredness is high) or (Tiredness is maximal) then (Target is sleep)");
MamdaniFuzzyRule rule3 = _fsAstronaut.ParseRule("if (Hunger is low) and (Thirst is low) and (Tiredness is low) then (Target is work)");
MamdaniFuzzyRule rule4 = _fsAstronaut.ParseRule("if (Hunger is normal) and (Thirst is normal) and (Tiredness is low) then (Target is work)");
//MamdaniFuzzyRule rule5 = _fsAstronaut.ParseRule("if (Hunger is minimal) and (Thirst is minimal) then (Target is not eat)");
_fsAstronaut.Rules.Add(rule2);
_fsAstronaut.Rules.Add(rule1);
_fsAstronaut.Rules.Add(rule3);
_fsAstronaut.Rules.Add(rule4);
//_fsAstronaut.Rules.Add(rule5);
System.Random rnd = new System.Random();
_stats.Stress = (float)rnd.NextDouble();
_stats.Agility = (float)rnd.NextDouble();
_stats.Strength = (float)rnd.NextDouble();
_stats.Health = 1f;
foreach (BaseModule module in Base.Instance.BaseModules)
{
if (module.HasFreeWorkingPlace)
{
currentLocation = module;
var workingPlaces = currentLocation.GetComponent <ModuleWorkingPlaces>();
transform.position = workingPlaces.ReserveWorkingPlace(this).position;
currentLocation.AstronautEnter(this);
break;
}
}
}