Example #1
0
        public override TSAFuzzySystem TuneUpFuzzySystem(TSAFuzzySystem Approx, ILearnAlgorithmConf conf)
        {
            TSAFuzzySystem 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);
        }
Example #2
0
        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);
        }
Example #3
0
        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);
        }
Example #4
0
        protected BeeParams lastStep(BeeParams theBest)
        {
            double tempgood = theBest.getGoodsImproove();
            KnowlegeBaseTSARules tempPositionofBee = theBest.PositionOfBee;
            TSAFuzzySystem       ToOpintNS         = getCurrentNs();
            KnowlegeBaseTSARules zeroSolution      = ToOpintNS.RulesDatabaseSet[0];

            ToOpintNS.RulesDatabaseSet[0] = theBest.PositionOfBee;

            RWLSMTakagiSugeno tryOpt = new RWLSMTakagiSugeno();

            tryOpt.TuneUpFuzzySystem(ToOpintNS, new NullConfForAll());

            theBest.PositionOfBee = ToOpintNS.RulesDatabaseSet[0];
            double newgood = theBest.getGoodsImproove();

            if (newgood > tempgood)
            {
                theBest.PositionOfBee = tempPositionofBee;
            }
            return(theBest);
        }
Example #5
0
 public virtual void flyOutLookers(BeeParams best, Random rand)
 {
     theOutlookers = OutLookersBeeParams.OutLookerFly(best, hostArchive, rand, theParrent);
 }
Example #6
0
 public virtual void flyWorkers(BeeParams best, Random rand)
 {
     theWorkers = WorkerParams.WorkersFly(best, hostArchive, rand, theParrent);
 }