예제 #1
0
파일: ANNTests.cs 프로젝트: chebz/ANNCsharp
        public void test1()
        {
            Console.WriteLine("Running test 1...");

            NeuronSettings nSettings = new NeuronSettings();
            NeuronLayerSettings layerSettings = new NeuronLayerSettings(nSettings);
            layerSettings.mNumNeuronsPerLayerMin = 2;
            layerSettings.mNumNeuronsPerLayerMax = 2;

            NeuronNetSettings nnSettings = new NeuronNetSettings(layerSettings);

            nnSettings.mNumInputs = 1;
            nnSettings.mNumOutputs = 1;
            nnSettings.mNumLayersMin = 0;
            nnSettings.mNumLayersMax = 0;

            GeneticAlgorithmSettings gaSettings = new GeneticAlgorithmSettings(nnSettings.mFactory);
            gaSettings.mMaxPopulation = 100;

            GeneticAlgorithm ga = new GeneticAlgorithm(gaSettings);

            List<double> inputs = new List<double>() { 0 };
            List<double> expected = new List<double>() { 0 };

            int mNumEpochs = 100;

            Console.WriteLine("Learning...");
            for (int iEpoch = 0; iEpoch < mNumEpochs; iEpoch++)
            {
                Console.Write(string.Format("Epoch: {0} / {1}\t", iEpoch + 1, mNumEpochs));

                for (int x = 0; x <= 100; x++)
                {
                    inputs.Clear();
                    expected.Clear();

                    inputs.Add((double)x / 100.0);
                    expected.Add((double)x / 100.0);
                    learnPopulation(ga, inputs, expected);
                }

                Console.Write(string.Format("Average: {0}\t", ga.AverageFitness));
                Console.Write(string.Format("Best: {0}\t", ga.BestFitness));
                Console.Write(string.Format("Worst: {0}\n", ga.WorstFitness));

                ga.epoch();
            }

            Console.WriteLine("Predicting...");

            for (int x = 0; x <= 100; x++)
            {
                inputs[0] = (double)x / 100.0;
                var outputs = predict(ga, inputs);
                Console.WriteLine(string.Format("Input:\t{0}\t\tOutput:\t{1}", inputs[0], outputs[0]));
            }
        }
예제 #2
0
 public NeuronNet(ObjectPool pool, NeuronNetSettings settings)
     : base(pool, settings)
 {
     mPool        = new ObjectPool(settings.mLayerSettings.mFactory, settings.mNumLayersMax);
     mOutputLayer = new NeuronLayer(mPool, settings.mLayerSettings);
 }
예제 #3
0
 public NeuronNetFactory(NeuronNetSettings nnSettings)
     : base(nnSettings)
 {
 }
예제 #4
0
 public NeuronNet(ObjectPool pool, NeuronNetSettings settings)
     : base(pool, settings)
 {
     mPool = new ObjectPool(settings.mLayerSettings.mFactory, settings.mNumLayersMax);
     mOutputLayer = new NeuronLayer(mPool, settings.mLayerSettings);
 }
예제 #5
0
파일: ANNTests.cs 프로젝트: chebz/ANNCsharp
        public void test5Thread()
        {
            Console.WriteLine("Running test 5, min...");

            DateTime timeStart = DateTime.Now;

            NeuronSettings nSettings = new NeuronSettings();
            NeuronLayerSettings layerSettings = new NeuronLayerSettings(nSettings);
            layerSettings.mNumNeuronsPerLayerMin = 2;
            layerSettings.mNumNeuronsPerLayerMax = 2;

            NeuronNetSettings nnSettings = new NeuronNetSettings(layerSettings);

            nnSettings.mNumInputs = 2;
            nnSettings.mNumOutputs = 1;
            nnSettings.mNumLayersMin = 2;
            nnSettings.mNumLayersMax = 2;

            GeneticAlgorithmSettings gaSettings = new GeneticAlgorithmSettings(nnSettings.mFactory);
            gaSettings.mMaxPopulation = 100;

            GeneticAlgorithm ga = new GeneticAlgorithm(gaSettings);

            List<double> inputs = new List<double>() { 0, 0 };
            List<double> expected = new List<double>() { 0 };

            int iEpoch = 0;

            Console.WriteLine("Learning...");
            while (!mLearningStopped && iEpoch < 100)
            {
                Console.Write(string.Format("Epoch: {0}\t", iEpoch++));

                for (double x = 0; x <= 1; x += 0.01)
                {
                    for (double y = 0; y <= 1; y += 0.01)
                    {
                        inputs[0] = x;
                        inputs[1] = y;

                        expected[0] = x*y;

                        learnPopulation(ga, inputs, expected);
                    }
                }

                Console.Write(string.Format("Average: {0:0.00}\t", ga.AverageFitness));
                Console.Write(string.Format("Best: {0:0.00}\t", ga.BestFitness));
                Console.Write(string.Format("Worst: {0:0.00}\n", ga.WorstFitness));

                ga.epoch();
            }
            DateTime timeEnd = DateTime.Now;
            TimeSpan ts = timeEnd - timeStart;
            Console.WriteLine("Learning took: " + ts.ToString());

            Console.WriteLine("Predicting...");

            for (double x = 0; x < 1; x += 0.1)
            {
                for (double y = 0; y < 1; y += 0.1)
                {
                    inputs[0] = x;
                    inputs[1] = y;
                    var outputs = predict(ga, inputs);
                    Console.WriteLine(string.Format("Input:\t{0}, {1}\t\tOutput:\t{2:0.000}", inputs[0], inputs[1], outputs[0]));
                }
            }
        }
예제 #6
0
파일: ANNTests.cs 프로젝트: chebz/ANNCsharp
        public void test4()
        {
            Console.WriteLine("Running test 4, cos...");

            NeuronSettings nSettings = new NeuronSettings();
            NeuronLayerSettings layerSettings = new NeuronLayerSettings(nSettings);
            layerSettings.mNumNeuronsPerLayerMin = 1;
            layerSettings.mNumNeuronsPerLayerMax = 1;

            NeuronNetSettings nnSettings = new NeuronNetSettings(layerSettings);

            nnSettings.mNumInputs = 1;
            nnSettings.mNumOutputs = 1;
            nnSettings.mNumLayersMin = 0;
            nnSettings.mNumLayersMax = 0;

            GeneticAlgorithmSettings gaSettings = new GeneticAlgorithmSettings(nnSettings.mFactory);
            gaSettings.mMaxPopulation = 1000;

            GeneticAlgorithm ga = new GeneticAlgorithm(gaSettings);

            List<double> inputs = new List<double>() { 0 };
            List<double> expected = new List<double>() { 0 };

            int mNumEpochs = 100;

            Console.WriteLine("Learning...");
            for (int iEpoch = 0; iEpoch < mNumEpochs; iEpoch++)
            {
                Console.Write(string.Format("Epoch: {0} / {1}\t", iEpoch + 1, mNumEpochs));

                for (double x = -1.5; x <= 1.5; x += 0.001)
                {
                    inputs[0] = x;
                    expected[0] = Math.Sin(x);
                    learnPopulation(ga, inputs, expected);
                }

                Console.Write(string.Format("Average: {0}\t", ga.AverageFitness));
                Console.Write(string.Format("Best: {0}\t", ga.BestFitness));
                Console.Write(string.Format("Worst: {0}\n", ga.WorstFitness));

                ga.epoch();
            }

            Console.Write(ga.SortedPopulation[0].ToString());
        }
예제 #7
0
 public NeuronNetFactory(NeuronNetSettings nnSettings)
     : base(nnSettings)
 {
 }