public override TSAFuzzySystem TuneUpFuzzySystem(TSAFuzzySystem Approx, ILearnAlgorithmConf conf)
// Здесь ведется оптимизация вашим алгоритмом
{
var first = true;
var WeedOriginal = new TSAFuzzySystemWithErrorKnowledgeBase(Approx);
double KLIRange = ((WeedsCut_conf)conf).Граница;
maxiter = ((WeedsCut_conf)conf).Количество_итераций;
var MaxUsingRule = ((WeedsCut_conf)conf).Максимально_потомков;
var MinUsingRule = ((WeedsCut_conf)conf).Минимально_потомков;
Random r = new Random();
while (first || Double.IsNaN((WeedOriginal.RulesDatabaseSet[0] as KnowlegeBaseTSARules).error))
{
int allUsingRuleCount = ((WeedsCut_conf)conf).Начальное_количество;
WeedOriginal = new TSAFuzzySystemWithErrorKnowledgeBase(Approx);
first = false;
List <int> list = new List <int>();
int counter = 0;
for (int i = 0; i < allUsingRuleCount; i++)
{
list.Add(counter);
counter++;
}
for (int i = 0; i < WeedOriginal.AcceptedFeatures.Count(); i++)
{
WeedOriginal.AcceptedFeatures[i] = false;
}
for (int i = 0; i < allUsingRuleCount; i++)
{
int index = r.Next(0, allUsingRuleCount - i);
int ddd = list[index];
WeedOriginal.AcceptedFeatures[ddd] = true;
list.RemoveAt(index);
}
global::KLI.KLI s = new global::KLI.KLI();
WeedOriginal = new TSAFuzzySystemWithErrorKnowledgeBase(s.Generate(WeedOriginal as TSAFuzzySystem, new KLI_conf()
{
MaxValue = KLIRange
}));
WeedOriginal.reinit();
(WeedOriginal.RulesDatabaseSet[0] as KnowlegeBaseTSARules).error = WeedOriginal.ErrorLearnSamples(WeedOriginal.RulesDatabaseSet[0]);
(WeedOriginal.RulesDatabaseSet[0] as KnowlegeBaseTSARules).RulesAcceptedFeatures = new List <bool>(WeedOriginal.AcceptedFeatures.ToList());
}
string added2 = (WeedOriginal.RulesDatabaseSet.Last() as KnowlegeBaseTSARules).RulesAcceptedFeatures.Aggregate(String.Empty, (current, v) => current + (" " + (v ? "1" : "0")));
File.AppendAllLines("./out2.txt", new List <string>()
{
WeedOriginal.RulesDatabaseSet.Last().RulesDatabase.Count + " " +
(WeedOriginal.RulesDatabaseSet.Last() as KnowlegeBaseTSARules).RulesAcceptedFeatures.Count(x => x) + " " + WeedOriginal.RMSEtoMSEforLearn(WeedOriginal.ErrorLearnSamples(WeedOriginal.RulesDatabaseSet.Last())) / 2 + " " + WeedOriginal.RMSEtoMSEforTest(WeedOriginal.ErrorTestSamples(WeedOriginal.RulesDatabaseSet.Last())) / 2 + " " + added2
});
Random rand = new Random();
for (int iter = 0; iter < maxiter; iter++)
{
List <KnowlegeBaseTSARules> newtstmp = new List <KnowlegeBaseTSARules>();
for (int k = 0; k < WeedOriginal.RulesDatabaseSet.Count; k++)
{
double fiBest = 1;
double fiWorst = (1 - (WeedOriginal.RulesDatabaseSet[k] as KnowlegeBaseTSARules).error);
if (!Double.IsNaN((WeedOriginal.RulesDatabaseSet[k] as KnowlegeBaseTSARules).error))
{
if (!Double.IsInfinity((WeedOriginal.RulesDatabaseSet[k] as KnowlegeBaseTSARules).error))
{
var CurrertChild =
Convert.ToInt32((MaxChild - MinChild) / (fiBest - fiWorst) * (1 - (WeedOriginal.RulesDatabaseSet[k] as KnowlegeBaseTSARules).error) +
(fiBest * MinChild - fiWorst * MaxChild) / (fiBest - fiWorst));
double delta = originalDelta * (maxiter - iter) / maxiter;
newtstmp.AddRange(WeedsCut.WeedsRegenerateIteration(WeedOriginal, (WeedOriginal.RulesDatabaseSet[k] as KnowlegeBaseTSARules), delta, rand, CurrertChild));
//
var item = newtstmp.Last();
item.RulesAcceptedFeatures = new List <bool>((WeedOriginal.RulesDatabaseSet[k] as KnowlegeBaseTSARules).RulesAcceptedFeatures);
for (int index = 0; index < item.RulesAcceptedFeatures.Count; index++)
{
if (Math.Sqrt(-2 * Math.Log(rand.NextDouble())) * Math.Cos(2 * Math.PI * rand.NextDouble()) > delta)
{
item.RulesAcceptedFeatures[index] = !item.RulesAcceptedFeatures[index];
}
}
while (item.RulesAcceptedFeatures.Count(x => x) > MaxUsingRule)
{
item.RulesAcceptedFeatures[(rand.Next(item.RulesAcceptedFeatures.Count))] = false;
}
while (item.RulesAcceptedFeatures.Count(x => x) < MinUsingRule)
{
item.RulesAcceptedFeatures[(rand.Next(item.RulesAcceptedFeatures.Count))] = true;
}
}
}
}
foreach (var weedBase in newtstmp)
{
RLS rls = new RLS();
var tmp = new TSAFuzzySystemWithErrorKnowledgeBase(WeedOriginal);
tmp.RulesDatabaseSet.Clear();
tmp.AcceptedFeatures = weedBase.RulesAcceptedFeatures.ToArray();
global::KLI.KLI s = new global::KLI.KLI();
tmp = s.Generate(tmp, new KLI_conf()
{
MaxValue = KLIRange
}) as TSAFuzzySystemWithErrorKnowledgeBase;
tmp.reinit();
(tmp.RulesDatabaseSet[0] as KnowlegeBaseTSARules).error = tmp.ErrorLearnSamples(tmp.RulesDatabaseSet[0]);
(tmp.RulesDatabaseSet[0] as KnowlegeBaseTSARules).RulesAcceptedFeatures = new List <bool>(tmp.AcceptedFeatures.ToList());
if (!double.IsNaN((tmp.RulesDatabaseSet[0] as KnowlegeBaseTSARules).error))
{
WeedOriginal.RulesDatabaseSet.Add(tmp.RulesDatabaseSet[0]);
string added = (tmp.RulesDatabaseSet[0] as KnowlegeBaseTSARules).RulesAcceptedFeatures.Aggregate(String.Empty, (current, v) => current + (" " + (v ? "1" : "0")));
File.AppendAllLines("./out2.txt", new List <string>()
{
tmp.RulesDatabaseSet[0].RulesDatabase.Count + " " +
(tmp.RulesDatabaseSet[0] as KnowlegeBaseTSARules).RulesAcceptedFeatures.Count(x => x) + " " + tmp.RMSEtoMSEforLearn(tmp.ErrorLearnSamples(tmp.RulesDatabaseSet[0])) / 2 + " " + tmp.RMSEtoMSEforTest(tmp.ErrorTestSamples(tmp.RulesDatabaseSet[0])) / 2 + " " + added
});
}
}
WeedOriginal.RulesDatabaseSet.RemoveAll(x => Double.IsInfinity((x as KnowlegeBaseTSARules).error) || Double.IsInfinity((x as KnowlegeBaseTSARules).error));
WeedOriginal.RulesDatabaseSet.Sort((c1, c2) => (c1 as KnowlegeBaseTSARules).error.CompareTo((c2 as KnowlegeBaseTSARules).error));
if (WeedOriginal.RulesDatabaseSet.Count > 6)
{
WeedOriginal.RulesDatabaseSet.RemoveRange(6, WeedOriginal.RulesDatabaseSet.Count - 6);
}
}
WeedOriginal.AcceptedFeatures = (WeedOriginal.RulesDatabaseSet[0] as KnowlegeBaseTSARules).RulesAcceptedFeatures.ToArray();
return(WeedOriginal);
}
public override TSAFuzzySystem TuneUpFuzzySystem(TSAFuzzySystem Approx, ILearnAlgorithmConf conf)
// Здесь ведется оптимизация вашим алгоритмом
{
Random rand = new Random();
SAFuzzySystem result = Approx;
var WeedOriginal = new TSAFuzzySystemWithErrorKnowledgeBase(Approx);
((KnowlegeBaseTSARulesWithError)WeedOriginal.RulesDatabaseSet[0]).error = WeedOriginal.ErrorLearnSamples(WeedOriginal.RulesDatabaseSet[0]);
maxiter = ((Weeds_conf)conf).Количество_итераций;
MaxChild = ((Weeds_conf)conf).Максимально_потомков;
MinChild = ((Weeds_conf)conf).Минимально_потомков;
originalDelta = ((Weeds_conf)conf).Дельта;
for (int iter = 0; iter < maxiter; iter++)
{
List <KnowlegeBaseTSARules> newtstmp = new List <KnowlegeBaseTSARules>();
for (int k = 0; k < WeedOriginal.RulesDatabaseSet.Count; k++)
{
double fiBest = 1;
double fiWorst = (1 - ((KnowlegeBaseTSARulesWithError)WeedOriginal.RulesDatabaseSet[k]).error);
if (!Double.IsNaN(((KnowlegeBaseTSARulesWithError)WeedOriginal.RulesDatabaseSet[k]).error))
{
if (!Double.IsInfinity(((KnowlegeBaseTSARulesWithError)WeedOriginal.RulesDatabaseSet[k]).error))
{
var CurrertChild =
Convert.ToInt32((MaxChild - MinChild) / (fiBest - fiWorst) * (1 - (((KnowlegeBaseTSARulesWithError)WeedOriginal.RulesDatabaseSet[k]).error)) +
(fiBest * MinChild - fiWorst * MaxChild) / (fiBest - fiWorst));
double delta = originalDelta * (maxiter - iter) / maxiter;
newtstmp.AddRange(Weeds.WeedsRegenerateIteration(WeedOriginal, WeedOriginal.RulesDatabaseSet[k], delta, rand, CurrertChild));
}
}
}
foreach (var weedBase in newtstmp)
{
RLS rls = new RLS();
TSAFuzzySystemWithErrorKnowledgeBase tmp = new TSAFuzzySystemWithErrorKnowledgeBase(WeedOriginal);
tmp.RulesDatabaseSet.Clear();
tmp.RulesDatabaseSet.Add(weedBase);
var errormnk = tmp.approxLearnSamples(tmp.RulesDatabaseSet[0]);
var rezMnk = rls.TuneUpFuzzySystem(tmp, new RLSconfig());
tmp.reinit();
((KnowlegeBaseTSARulesWithError)tmp.RulesDatabaseSet[0]).error = rezMnk.approxLearnSamples(rezMnk.RulesDatabaseSet[0]);
if (tmp.approxLearnSamples(tmp.RulesDatabaseSet[0]) < tmp.approxLearnSamples(tmp.RulesDatabaseSet[1]))
{
WeedOriginal.RulesDatabaseSet.Add(tmp.RulesDatabaseSet[0]);
}
else
{
WeedOriginal.RulesDatabaseSet.Add(tmp.RulesDatabaseSet[1]);
}
}
WeedOriginal.RulesDatabaseSet.RemoveAll(x => Double.IsInfinity(((KnowlegeBaseTSARulesWithError)x).error) || Double.IsInfinity(((KnowlegeBaseTSARulesWithError)x).error));
WeedOriginal.RulesDatabaseSet.Sort((c1, c2) => ((KnowlegeBaseTSARulesWithError)c1).error.CompareTo(((KnowlegeBaseTSARulesWithError)c2).error));
if (WeedOriginal.RulesDatabaseSet.Count > 6)
{
WeedOriginal.RulesDatabaseSet.RemoveRange(6, WeedOriginal.RulesDatabaseSet.Count - 6);
}
}
return(WeedOriginal);
}