static void Main(string[] args) {
FeedforwardNetwork network = new FeedforwardNetwork();
network.AddLayer(new FeedforwardLayer(2));
network.AddLayer(new FeedforwardLayer(3));
network.AddLayer(new FeedforwardLayer(1));
network.Reset();
// train the neural network
TrainingSetNeuralGeneticAlgorithm train = new TrainingSetNeuralGeneticAlgorithm(
network, true, XOR_INPUT, XOR_IDEAL, 5000, 0.1, 0.25);
int epoch = 1;
do {
train.Iteration();
Console.WriteLine("Epoch #" + epoch + " Error:" + train.Error);
epoch++;
} while ((epoch < 5000) && (train.Error > 0.001));
network = train.Network;
// test the neural network
Console.WriteLine("Neural Network Results:");
for (int i = 0; i < XOR_IDEAL.Length; i++) {
double []actual = network.ComputeOutputs(XOR_INPUT[i]);
Console.WriteLine(XOR_INPUT[i][0] + "," + XOR_INPUT[i][1]
+ ", actual=" + actual[0] + ",ideal=" + XOR_IDEAL[i][0]);
}
}
/// <summary>
/// The constructor sets up to train the neural network with a GA.
/// </summary>
/// <param name="genetic">The genetic algorithm to use.</param>
/// <param name="network">The neural network to use.</param>
public TrainingSetNeuralChromosome(
TrainingSetNeuralGeneticAlgorithm genetic,
FeedforwardNetwork network)
{
this.GA = genetic;
this.Network = network;
InitGenes(network.MatrixSize);
UpdateGenes();
}
/// <summary>
/// The constructor sets up to train the neural network with a GA.
/// </summary>
/// <param name="genetic">The genetic algorithm to use.</param>
/// <param name="network">The neural network to use.</param>
public TrainingSetNeuralChromosome(
TrainingSetNeuralGeneticAlgorithm genetic,
FeedforwardNetwork network)
{
this.GA = genetic;
this.Network = network;
InitGenes(network.MatrixSize);
UpdateGenes();
}
