public WinnerDistance(double dist, SOM.Neuron neuron)
{
winner = neuron;
distance = dist;
}
//public static void Main()
//{
// // Crossover = 80%
// // Mutation = 5%
// // Population size = 100
// // Generations = 2000
// // Genome size = 2
// GA ga = new GA(0.8, 0.05, 100, 2000, 2);
// ga.FitnessFunction = new GAFunction(theActualFunction);
// //ga.FitnessFile = @"H:\fitness.csv";
// ga.Elitism = true;
// ga.Go();
// double[] values;
// double fitness;
// ga.GetBest(out values, out fitness);
// System.Console.WriteLine("Best ({0}):", fitness);
// for (int i = 0; i < values.Length; i++)
// System.Console.WriteLine("{0} ", values[i]);
// //ga.GetWorst(out values, out fitness);
// //System.Console.WriteLine("\nWorst ({0}):", fitness);
// //for (int i = 0 ; i < values.Length ; i++)
// // System.Console.WriteLine("{0} ", values[i]);
// System.Console.ReadLine();
//}
private void Initialise()
{
iteration = 0;
outputs = null;
outputs = new SOM.Neuron[length, length];
for (int i = 0; i < length; i++)
{
for (int j = 0; j < length; j++)
{
outputs[i, j] = new SOM.Neuron(i, j, length);
outputs[i, j].Weights = new double[dimensions];
for (int k = 0; k < dimensions; k++)
{
outputs[i, j].Weights[k] = rnd.NextDouble();
}
}
}
}
