public virtual void Final()
{
theFuzzySystem.RulesDatabaseSet[0] = Best;
baseLine = theFuzzySystem.ErrorLearnSamples(theFuzzySystem.RulesDatabaseSet[0]);
// theScouts = null;
// theWorkers = null;
// theScout = null;
// theWorker = null;
GC.Collect();
}
public virtual void oneIterate(FS result)
{
theScouts.Clear();
theWorkers.Clear();
baseLine = result.ErrorLearnSamples(result.RulesDatabaseSet[0]);
Best = result.RulesDatabaseSet[0];
theScout = null;
theWorker = null;
for (int s = 0; s < countScouts; s++)
{
double goodsLine = -1;
int ztryes = 0;
while ((goodsLine <= 0) && (ztryes < 100))
{
theScout = new Scout(Best, theFuzzySystem);
theScout.generateNewRule(typeTerm, rand);
goodsLine = theScout.getGoodsImproove(baseLine);
}
theScouts.Add(theScout);
}
BeeComparer toBeeSort = new BeeComparer();
theScouts.Sort(toBeeSort);
KnowlegeBaseRules ScoutBest = theScouts[theScouts.Count - 1].PositionOfBee;
int ScoutBestNumRule = theScouts[theScouts.Count - 1].NumOFRule;
for (int w = 0; w < countWorkers; w++)
{
theWorker = new Worker(ScoutBest, theFuzzySystem);
theWorkers.Add(theWorker);
theWorkers[theWorkers.Count - 1].WorkerFly(ScoutBestNumRule, rand);
theWorkers[theWorkers.Count - 1].getGoodsImproove(baseLine);
}
theWorkers.Sort(toBeeSort);
if (theScouts[theScouts.Count - 1].Goods > theWorkers[theWorkers.Count - 1].Goods)
{
Best = theScouts[theScouts.Count - 1].PositionOfBee;
}
else
{
Best = theWorkers[theWorkers.Count - 1].PositionOfBee;
}
theFuzzySystem.RulesDatabaseSet[0] = Best;
}
public virtual void oneIterate(FS result)
{
// theScouts.Clear();
// theWorkers.Clear();
baseLine = result.ErrorLearnSamples(result.RulesDatabaseSet[0]);
Best = result.RulesDatabaseSet[0];
/* for (int s = 0; s < countScouts; s++)
* {
* double goodsLine = -1;
* int ztryes = 0;
* while ((goodsLine <= 0) && (ztryes < 100))
* {
* theScout = new Scout(Best, theFuzzySystem);
* theScout.generateNewRule(typeTerm, rand);
* goodsLine = theScout.getGoodsImproove(baseLine);
* ztryes++;
* }
* theScouts.Add(theScout);
* }*/
Parallel.For(0, countScouts, new ParallelOptions {
MaxDegreeOfParallelism = countScouts, TaskScheduler = null
}, s =>
// for (int s = 0; s < countScouts; s++)
{
double goodsLine = -1;
int ztryes = 0;
while ((goodsLine <= 0) && (ztryes < 100))
{
theScouts[s] = new Scout(Best, theFuzzySystem);
theScouts[s].generateNewRule(typeTerm, rand.Value);
goodsLine = theScouts[s].getGoodsImproove(baseLine);
ztryes++;
}
}
);
BeeComparer toBeeSort = new BeeComparer();
Array.Sort(theScouts, toBeeSort);
KnowlegeBaseRules ScoutBest = theScouts[countScouts - 1].PositionOfBee;
int ScoutBestNumRule = theScouts[countScouts - 1].NumOFRule;
/*for (int w = 0; w < countWorkers; w++)
* {
* theWorker = new Worker(ScoutBest, theFuzzySystem);
* theWorkers.Add(theWorker);
* theWorkers[theWorkers.Count - 1].WorkerFly( ScoutBestNumRule, rand);
* theWorkers[countWorkers*3 - 1].getGoodsImproove(baseLine);
* }*/
for (int a = 0; a < 3; a++)
{
Parallel.For(0, countWorkers, new ParallelOptions {
MaxDegreeOfParallelism = countWorkers, TaskScheduler = null
}, w =>
// for (int w = 0; w < countWorkers; w++)
{
theWorkers[countWorkers * a + w] = new Worker(theScouts[theScouts.Length - 1 - a].PositionOfBee, theFuzzySystem);
theWorkers[countWorkers * a + w].WorkerFly(ScoutBestNumRule, rand.Value);
theWorkers[countWorkers * a + w].getGoodsImproove(baseLine);
}
);
}
Array.Sort(theWorkers, toBeeSort);
if (theScouts[countScouts - 1].Goods > theWorkers[countWorkers * 3 - 1].Goods)
{
Best = theScouts[countScouts - 1].PositionOfBee;
}
else
{
Best = theWorkers[countWorkers * 3 - 1].PositionOfBee;
}
theFuzzySystem.RulesDatabaseSet[0] = Best;
}
public double getGoodsImproove(double baseValue)
{
goods = baseValue - Parrent.ErrorLearnSamples(thePositionOfBee);
return(goods);
}