public void SetInput(double[] inputArray)
{
if (_network.InputLayer == null)
{
_network.SetInputLayer(inputArray);
}
else
{
_network.SetInputLayer(inputArray);
}
}
private void NearGenesCrossWithOffspring(NeuronNet individualA, NeuronNet individualB)
{
NeuronNet offspring = new NeuronNet(Shape, Rnd);
double extraRange = 0.1;
offspring.SetInputLayer(InputExample);
if (individualA.Layers.Count != individualB.Layers.Count)
{
throw new Exception("Different layer size. Can not cross");
}
for (int i = 0; i < individualA.Layers.Count; i++)
{
if (individualA.Layers[i].Neurons.Count != individualB.Layers[i].Neurons.Count)
{
throw new Exception("Different neuron size. Can not cross");
}
for (int j = 0; j < individualA.Layers[i].Neurons.Count; j++)
{
double auxBiasA = individualA.Layers[i].Neurons[j].Bias;
double auxBiasB = individualB.Layers[i].Neurons[j].Bias;
double maximumBias;
double minimumBias;
if (auxBiasA > auxBiasB)
{
maximumBias = auxBiasA + (auxBiasA * extraRange);
minimumBias = auxBiasB - (auxBiasA * extraRange);
}
else
{
maximumBias = auxBiasB + (auxBiasA * extraRange);
minimumBias = auxBiasA - (auxBiasA * extraRange);
}
offspring.Layers[i].Neurons[j].Bias = Rnd.NextDouble() * (maximumBias - minimumBias) + minimumBias;
if (individualA.Layers[i].Neurons[j].Dendrites.Count != individualB.Layers[i].Neurons[j].Dendrites.Count)
{
throw new Exception("Different dendrite count. Can not cross");
}
for (int k = 0; k < individualA.Layers[i].Neurons[j].Dendrites.Count; k++)
{
double auxDendriteWeightA = individualA.Layers[i].Neurons[j].Dendrites[k].Weight;
double auxDendriteWeightB = individualB.Layers[i].Neurons[j].Dendrites[k].Weight;
double maximum;
double minimum;
if (auxDendriteWeightA > auxDendriteWeightB)
{
maximum = auxDendriteWeightA + (auxDendriteWeightA * extraRange);
minimum = auxDendriteWeightB - (auxDendriteWeightA * extraRange);
}
else
{
maximum = auxDendriteWeightB + (auxDendriteWeightA * extraRange);
minimum = auxDendriteWeightA - (auxDendriteWeightA * extraRange);
}
offspring.Layers[i].Neurons[j].Dendrites[k].Weight = Rnd.NextDouble() * (maximum - minimum) + minimum;
}
}
}
PopulationList.Add(offspring);
}