public SAFuzzySystem(SAFuzzySystem Source)
: base(Source)
{
RulesDatabaseSet = new List <KnowlegeBaseSARules>();
for (int i = 0; i < Source.RulesDatabaseSet.Count; i++)
{
RulesDatabaseSet.Add(new KnowlegeBaseSARules(Source.RulesDatabaseSet[i]));
}
}
public static double NearestApprox(SAFuzzySystem Approximate, List <Term> termSet)
{
double min_diff = double.PositiveInfinity;
int min_diff_index = 0;
for (int c = 0; c < Approximate.LearnSamplesSet.CountSamples; c++)
{
double current_diff = 0;
for (int i = 0; i < termSet.Count; i++)
{
if (Approximate.AcceptedFeatures[termSet[i].NumVar] == false)
{
continue;
}
if (termSet[i] != null)
{
switch (termSet[i].TermFuncType)
{
case TypeTermFuncEnum.Треугольник:
current_diff +=
Math.Abs(Approximate.LearnSamplesSet.DataRows[c].InputAttributeValue[termSet[i].NumVar] -
termSet[i].Parametrs[1]);
break;
case TypeTermFuncEnum.Гауссоида: current_diff +=
Math.Abs(Approximate.LearnSamplesSet.DataRows[c].InputAttributeValue[termSet[i].NumVar] -
termSet[i].Parametrs[0]);
break;
case TypeTermFuncEnum.Парабола:
double argv = (termSet[i].Parametrs[0] + termSet[i].Parametrs[1]) / 2;
current_diff +=
Math.Abs(Approximate.LearnSamplesSet.DataRows[c].InputAttributeValue[termSet[i].NumVar] -
argv);
break;
case TypeTermFuncEnum.Трапеция: double argvTR = (termSet[i].Parametrs[1] + termSet[i].Parametrs[2]) / 2;
current_diff +=
Math.Abs(Approximate.LearnSamplesSet.DataRows[c].InputAttributeValue[termSet[i].NumVar] -
argvTR);
break;
}
}
}
if (current_diff < min_diff)
{
min_diff = current_diff;
min_diff_index = c;
}
}
return(Approximate.LearnSamplesSet.DataRows[min_diff_index].DoubleOutput);
}
public void constuct__and_add_the_Rule(List <Term> terms, SAFuzzySystem FS)
{
SARule Result;
int[] order_of_terms = new int[terms.Count()];
for (int i = 0; i < terms.Count(); i++)
{
order_of_terms[i] = TermsSet.Count;
TermsSet.Add(terms[i]);
}
double kons_Value = KNNConsequent.NearestApprox(FS, TermsSet);
Result = new SARule(TermsSet, order_of_terms, kons_Value);
RulesDatabase.Add(Result);
}
public static double NearestApprox(SAFuzzySystem Approximate, TermSetGlobal <Term> termSet)
{
return(NearestApprox(Approximate, termSet.ToList()));
}
public override FuzzySystem.SingletoneApproximate.SAFuzzySystem TuneUpFuzzySystem(FuzzySystem.SingletoneApproximate.SAFuzzySystem Approximate, ILearnAlgorithmConf conf)
{
result = Approximate;
Init(conf);
Ocean = new SingletonHybride(new SAFuzzySystem(result));
List <Task> AlgTasks = new List <Task>();
Parallel.For(0, Configs.Count, magic =>
{
Task CurrentTask = new Task(() => { Algorithms[magic].TuneUpFuzzySystem(Ocean, new SAFuzzySystem(result), Configs[magic]); });
AlgTasks.Add(CurrentTask);
AlgTasks[magic].Start();
}
);
Task.WaitAll(AlgTasks.ToArray());
List <KnowlegeBaseSARules> ListSystems = Ocean.Get(1, FuzzySystem.FuzzyAbstract.Hybride.FuzzyHybrideBase.goodness.best, FuzzySystem.FuzzyAbstract.Hybride.FuzzyHybrideBase.islandStrategy.All);
ListSystems.Add(result.RulesDatabaseSet[0]);
result.RulesDatabaseSet[0] = ListSystems.SelectBest(result, 1)[0];
result.RulesDatabaseSet[0].TermsSet.Trim();
return(result);
}
