public static List<FuzzyVariable> Stretch(
List<MeasurementWithResult> learningSet,
DecisionMakerType1 originalDecisionMaker,
VariableMFParam toStretch,
BoundType boundType)
{
List<MeasurementWithResult> withResultsFromFs = (from measurement in learningSet
select
new MeasurementWithResult
{
InputValues = new Dictionary<string, double>(measurement.InputValues),
OutputString = originalDecisionMaker.InferTerm(measurement.InputValues)
}).ToList();
double multiplier = 1;
int error = 0;
bool canStretchMore = true;
if (boundType == BoundType.Upper)
{
while (error == 0 && canStretchMore)
{
multiplier += 0.001;
MamdaniFuzzySystem newFuzzySystem = UpdateParamsByMultiplier(
originalDecisionMaker,
multiplier,
toStretch,
out canStretchMore);
var updatedDecisionMaker = new DecisionMakerType1(newFuzzySystem, originalDecisionMaker.RulesDefinitions);
error = (from measurement in withResultsFromFs
where updatedDecisionMaker.InferTerm(measurement.InputValues) != measurement.OutputString
select measurement).Count();
}
multiplier -= 0.001;
var finalFuzzySystem = UpdateParamsByMultiplier(
originalDecisionMaker,
multiplier,
toStretch,
out canStretchMore);
return finalFuzzySystem.Input;
}
else
{
while (error == 0 && canStretchMore)
{
multiplier -= 0.001;
MamdaniFuzzySystem newFuzzySystem = UpdateParamsByMultiplier(
originalDecisionMaker,
multiplier,
toStretch,
out canStretchMore);
var updatedDecisionMaker = new DecisionMakerType1(newFuzzySystem, originalDecisionMaker.RulesDefinitions);
error = (from measurement in withResultsFromFs
where updatedDecisionMaker.InferTerm(measurement.InputValues) != measurement.OutputString
select measurement).Count();
}
multiplier += 0.001;
var finalFuzzySystem = UpdateParamsByMultiplier(
originalDecisionMaker,
multiplier,
toStretch,
out canStretchMore);
return finalFuzzySystem.Input;
}
}
private static MamdaniFuzzySystem UpdateParamsByMultiplier(
DecisionMakerType1 originalDecisionMaker,
double multiplier,
VariableMFParam paramToUpdate,
out bool canStretchMore)
{
canStretchMore = false;
// Create empty fuzzy system
MamdaniFuzzySystem newFs = new MamdaniFuzzySystem();
// Create input and output variables for the system
foreach (var inputVariable in originalDecisionMaker.fsWellEval.Input)
{
FuzzyVariable fsVariable = new FuzzyVariable(inputVariable.Name, inputVariable.Min, inputVariable.Max);
foreach (var term in inputVariable.Terms)
{
var mf = term.MembershipFunction as NormalMembershipFunction;
if (paramToUpdate == VariableMFParam.Mean)
{
if (mf != null && (mf.B * multiplier >= fsVariable.Min && mf.B * multiplier <= fsVariable.Max))
{
fsVariable.Terms.Add(
new FuzzyTerm(term.Name, new NormalMembershipFunction(mf.B * multiplier, mf.Sigma)));
canStretchMore = true;
}
else
{
if (mf != null)
{
fsVariable.Terms.Add(new FuzzyTerm(term.Name, new NormalMembershipFunction(mf.B, mf.Sigma)));
canStretchMore = false;
}
}
}
if (paramToUpdate == VariableMFParam.Deviation)
{
if (mf != null && (mf.Sigma * multiplier >= 0.001 && mf.Sigma * multiplier <= 10))
{
fsVariable.Terms.Add(
new FuzzyTerm(term.Name, new NormalMembershipFunction(mf.B, mf.Sigma * multiplier)));
}
else
{
if (mf != null)
{
fsVariable.Terms.Add(new FuzzyTerm(term.Name, new NormalMembershipFunction(mf.B, mf.Sigma)));
}
}
}
if (paramToUpdate == VariableMFParam.RuleWeight)
{
if (mf != null)
{
fsVariable.Terms.Add(new FuzzyTerm(term.Name, new NormalMembershipFunction(mf.B, mf.Sigma)));
}
}
}
newFs.Input.Add(fsVariable);
}
foreach (var outputVariable in originalDecisionMaker.fsWellEval.Output)
{
var newVariable = new FuzzyVariable(
outputVariable.Name,
outputVariable.Min,
outputVariable.Max,
outputVariable.Unit);
newVariable.Terms.Clear();
newVariable.Terms.AddRange(outputVariable.Terms);
newFs.Output.Add(newVariable);
}
for (int i = 0; i < originalDecisionMaker.RulesDefinitions.Items.Count; i++)
{
MamdaniFuzzyRule newRule = newFs.ParseRule(originalDecisionMaker.RulesDefinitions.Items[i].Definition);
double oldWeight = originalDecisionMaker.fsWellEval.Rules[i].Weight;
if (paramToUpdate == VariableMFParam.RuleWeight)
{
if (oldWeight * multiplier >= 0.001 && oldWeight * multiplier <= 1)
{
newRule.Weight = oldWeight * multiplier;
}
}
else
{
newRule.Weight = oldWeight;
}
newFs.Rules.Add(newRule);
}
return newFs;
}
private void UpdateMemberships(List<FuzzyVariable> sourceVariables, VariableMFParam parameterToUpdate, BoundType boundType)
{
switch (parameterToUpdate)
{
case VariableMFParam.Mean:
case VariableMFParam.Deviation:
foreach (var variable in inputVariables)
{
foreach (var type2term in variable.Terms)
{
var sourceTerm = sourceVariables.Find(v => v.Name == variable.Name).Terms.Find(t => t.Name == type2term.Name);
var mf = sourceTerm.MembershipFunction as NormalMembershipFunction;
if (boundType == BoundType.Lower)
{
type2term.LowerMembershipFunction = new NormalMembershipFunction(mf.B, mf.Sigma);
}
else
{
type2term.UpperMembershipFunction = new NormalMembershipFunction(mf.B, mf.Sigma);
}
}
}
break;
case VariableMFParam.RuleWeight:
// todo
break;
}
}