public override SAFuzzySystem TuneUpFuzzySystem(SAFuzzySystem Approx, ILearnAlgorithmConf conf)
{
SAFuzzySystem result = Approx;
BeeParamsConf Config = conf as BeeParamsConf;
Init(Config);
theFuzzySystem = result;
if (result.RulesDatabaseSet.Count < 1)
{
throw (new Exception("Что то не так с базой правил"));
}
theHive = new HiveParams(this, result.RulesDatabaseSet[0]);
// HiveParams theHive = new ParallelHiveParams(this, result.RulesDatabaseSet[0]);
// HiveParams theHive = new HiveParallelParams2(this, result.RulesDatabaseSet[0]);
theBest = new BeeParams(result.RulesDatabaseSet[0], this);
double temperature = initTemp;
for (int r = 0; r < iterration; r++)
{
temperature = oneIterate(temperature);
GC.Collect();
}
theBest = lastStep(theBest);
Approx.RulesDatabaseSet[0] = theBest.PositionOfBee;
Approx.RulesDatabaseSet[0].TermsSet.Trim();
return(Approx);
}
public static List <BeeParams> OutLookerFly(BeeParams Best, List <BeeParams> Source, Random rand, BeeParamsAlgorithm parrent)
{
List <BeeParams> Result = new List <BeeParams>();
for (int i = 0; i < Source.Count(); i++)
{
Result.Add(new OutLookersBeeParams(Source[i].PositionOfBee, Best.PositionOfBee, parrent, rand));
}
return(Result);
}
public new static List <BeeParams> WorkersFly(BeeParams Best, List <BeeParams> Source, Random rand, BeeParamsAlgorithm parrent)
{
List <BeeParams> Result = new List <BeeParams>();
Parallel.For(0, Source.Count, (int i) =>
{
Result.Add(new WorkerParams(Source[i].PositionOfBee, Best.PositionOfBee, parrent, rand));
});
return(Result);
}
public double oneIterate(double temperature)
{
theHive.flyScouts(countScouts, rand, theBest.PositionOfBee);
double newtemperature = theHive.LimitScoutBeeSolution(temperature, coefTemp, rand);
theBest = theHive.findBestinHive();
theHive.flyWorkers(theBest, rand);
theHive.flyOutLookers(theBest, rand);
countScouts = theHive.makeNewPopulation(TypeSelection, hiveSize, persentScouts, rand, border1, border2, border3, repeat1, repeat2, repeat3);
theBest = theHive.findBestinHive();
return(newtemperature);
}
public SAFuzzySystem TuneUpFuzzySystem(SingletonHybride Ocean, SAFuzzySystem Approximate, ILearnAlgorithmConf conf)
{
SAFuzzySystem result = Approximate;
BeeParamsConf Config = conf as BeeParamsConf;
Init(Config);
theFuzzySystem = result;
if (result.RulesDatabaseSet.Count < 1)
{
throw (new Exception("Что то не так с базой правил"));
}
theHive = new HiveParams(this, result.RulesDatabaseSet[0]);
// HiveParams theHive = new ParallelHiveParams(this, result.RulesDatabaseSet[0]);
// HiveParams theHive = new HiveParallelParams2(this, result.RulesDatabaseSet[0]);
theBest = new BeeParams(result.RulesDatabaseSet[0], this);
double temperature = initTemp;
for (int r = 0; r < iterration; r++)
{
temperature = oneIterate(temperature);
int CountSend = theHive.HostArchive.Count / 2;
List <KnowlegeBaseSARules> toStore = new List <KnowlegeBaseSARules>();
for (int i = 0; i < CountSend; i++)
{
toStore.Add(theHive.HostArchive[i].PositionOfBee);
}
Ocean.Store(toStore, this.ToString());
int toGet = theHive.HostArchive.Count - CountSend;
List <KnowlegeBaseSARules> Getted = Ocean.Get(toGet, FuzzyAbstract.Hybride.FuzzyHybrideBase.goodness.best, FuzzyAbstract.Hybride.FuzzyHybrideBase.islandStrategy.All);
toGet = Getted.Count < toGet ? Getted.Count : toGet;
for (int i = 0; i < toGet; i++)
{
theHive.HostArchive[i + CountSend].PositionOfBee = Getted[i];
}
GC.Collect();
}
theBest = lastStep(theBest);
Approximate.RulesDatabaseSet[0] = theBest.PositionOfBee;
return(result);
}
protected BeeParams lastStep(BeeParams theBest)
{
Adaptive_LSM tryOpt = new Adaptive_LSM();
double tempgood = theBest.getGoodsImproove();
KnowlegeBaseSARules tempPositionofBee = theBest.PositionOfBee;
SAFuzzySystem ToOpintNS = getCurrentNs();
KnowlegeBaseSARules zeroSolution = ToOpintNS.RulesDatabaseSet[0];
ToOpintNS.RulesDatabaseSet[0] = theBest.PositionOfBee;
tryOpt.TuneUpFuzzySystem(ToOpintNS, new NullConfForAll());
theBest.PositionOfBee = ToOpintNS.RulesDatabaseSet[0];
double newgood = theBest.getGoodsImproove();
if (newgood > tempgood)
{
theBest.PositionOfBee = tempPositionofBee;
}
return(theBest);
}
public override void flyWorkers(BeeParams best, Random rand)
{
Thread[] threads = new Thread[2];
threads[0] = new Thread(() => { theWorkers = ParralelWorkerParams.WorkersFly(best, hostArchive, rand, theParrent); });
threads[1] = new Thread(() => { theOutlookers = ParallelOultLookersBeeParams.OutLookerFly(best, hostArchive, rand, theParrent); });
try
{
threads[0].Start();
threads[1].Start();
}
catch (Exception)
{
}
while (threads[0].IsAlive || threads[1].IsAlive)
{
// Thread.Sleep(10);
}
}
public override void flyOutLookers(BeeParams best, Random rand)
{
}
public virtual void flyOutLookers(BeeParams best, Random rand)
{
theOutlookers = OutLookersBeeParams.OutLookerFly(best, hostArchive, rand, theParrent);
}
public virtual void flyWorkers(BeeParams best, Random rand)
{
theWorkers = WorkerParams.WorkersFly(best, hostArchive, rand, theParrent);
}
public override void flyOutLookers(BeeParams best, Random rand)
{
theOutlookers = ParallelOultLookersBeeParams.OutLookerFly(best, hostArchive, rand, theParrent);
}
public override void flyWorkers(BeeParams best, Random rand)
{
theWorkers = ParralelWorkerParams.WorkersFly(best, hostArchive, rand, theParrent);
}
