public NeuralNetwork[] Mutate(NeuralNetwork[] neuralNetworkArgs, int percentAmountMutate, int percentMutate)
{
List <NeuralNetwork> neuralNetwork = new List <NeuralNetwork>();
NeuralNetwork neuralNetworkMethods = new NeuralNetwork(0, 0, 0);
int randomInt = random.Next(101);
for (int x = 0; x < neuralNetworkArgs.Length; x++)
{
if (randomInt < percentAmountMutate)
{
List <Neuron> input = new List <Neuron>(), hidden = new List <Neuron>(), output = new List <Neuron>();
randomInt = random.Next(101);
for (int y = 0; y < neuralNetworkArgs[x].input.Length; y++)
{
if (randomInt < percentMutate)
{
input.Add(neuralNetworkMethods.MutateNeuron(neuralNetworkArgs[x].input[y], neuralNetworkArgs[x].hidden));
}
else
{
input.Add(neuralNetworkArgs[x].input[y]);
}
randomInt = random.Next(101);
}
for (int y = 0; y < neuralNetworkArgs[x].hidden.Length; y++)
{
if (randomInt < percentMutate)
{
hidden.Add(neuralNetworkMethods.MutateNeuron(neuralNetworkArgs[x].hidden[y], neuralNetworkArgs[x].output));
}
else
{
hidden.Add(neuralNetworkArgs[x].hidden[y]);
}
randomInt = random.Next(101);
}
foreach (Neuron neuron in neuralNetworkArgs[x].output)
{
output.Add(neuron);
}
neuralNetwork.Add(new NeuralNetwork(input.Count, hidden.Count, output.Count));
neuralNetwork[x].EstablishExistingNetwork(input.ToArray(), hidden.ToArray(), output.ToArray());
}
else
{
neuralNetwork.Add(neuralNetworkArgs[x]);
}
randomInt = random.Next(101);
}
return(neuralNetwork.ToArray());
}
public NeuralNetwork[] AddHidden(NeuralNetwork[] neuralNetworkArgs, int percentNegative, int percentHidden)
{
List <NeuralNetwork> neuralNetwork = new List <NeuralNetwork>();
NeuralNetwork neuralNetworkMethods = new NeuralNetwork(0, 0, 0);
int randomInt = random.Next(101);
for (int x = 0; x < neuralNetworkArgs.Length; x++)
{
if (randomInt < percentHidden)
{
List <Neuron> input = new List <Neuron>(), hidden = new List <Neuron>(), output = new List <Neuron>();
foreach (Neuron neuronArgs in neuralNetworkArgs[x].input)
{
input.Add(neuronArgs);
}
foreach (Neuron neuronArgs in neuralNetworkArgs[x].output)
{
output.Add(neuronArgs);
}
for (int y = 0; y < neuralNetworkArgs[x].hidden.Length; y++)
{
hidden.Add(neuralNetworkArgs[x].hidden[y]);
if (y == neuralNetworkArgs[x].hidden.Length - 1)
{
if (randomInt < percentNegative)
{
hidden.Add(neuralNetworkMethods.CreateHidden(neuralNetworkArgs[x].hidden.Length, true));
}
else
{
hidden.Add(neuralNetworkMethods.CreateHidden(neuralNetworkArgs[x].hidden.Length, false));
}
neuralNetworkMethods.MutateNeuron(hidden[y + 1], output.ToArray());
neuralNetworkMethods.ConnectInput(input.ToArray(), hidden[y + 1]);
}
}
neuralNetwork.Add(new NeuralNetwork(input.Count, hidden.Count, output.Count));
neuralNetwork[x].EstablishExistingNetwork(input.ToArray(), hidden.ToArray(), output.ToArray());
}
else
{
neuralNetwork.Add(neuralNetworkArgs[x]);
}
randomInt = random.Next(101);
}
return(neuralNetwork.ToArray());
}
public NeuralNetwork[] AddHidden(NeuralNetwork[] neuralNetworkArgs, int percentNegative, int percentHidden)
{
List<NeuralNetwork> neuralNetwork = new List<NeuralNetwork>();
NeuralNetwork neuralNetworkMethods = new NeuralNetwork(0, 0, 0);
int randomInt = random.Next(101);
for (int x = 0; x < neuralNetworkArgs.Length; x++)
{
if (randomInt < percentHidden)
{
List<Neuron> input = new List<Neuron>(), hidden = new List<Neuron>(), output = new List<Neuron>();
foreach (Neuron neuronArgs in neuralNetworkArgs[x].input)
input.Add(neuronArgs);
foreach (Neuron neuronArgs in neuralNetworkArgs[x].output)
output.Add(neuronArgs);
for (int y = 0; y < neuralNetworkArgs[x].hidden.Length; y++)
{
hidden.Add(neuralNetworkArgs[x].hidden[y]);
if (y == neuralNetworkArgs[x].hidden.Length - 1)
{
if (randomInt < percentNegative)
hidden.Add(neuralNetworkMethods.CreateHidden(neuralNetworkArgs[x].hidden.Length, true));
else
hidden.Add(neuralNetworkMethods.CreateHidden(neuralNetworkArgs[x].hidden.Length, false));
neuralNetworkMethods.MutateNeuron(hidden[y + 1], output.ToArray());
neuralNetworkMethods.ConnectInput(input.ToArray(), hidden[y + 1]);
}
}
neuralNetwork.Add(new NeuralNetwork(input.Count, hidden.Count, output.Count));
neuralNetwork[x].EstablishExistingNetwork(input.ToArray(), hidden.ToArray(), output.ToArray());
}
else
{
neuralNetwork.Add(neuralNetworkArgs[x]);
}
randomInt = random.Next(101);
}
return neuralNetwork.ToArray();
}
public NeuralNetwork[] Mutate(NeuralNetwork[] neuralNetworkArgs, int percentAmountMutate, int percentMutate)
{
List<NeuralNetwork> neuralNetwork = new List<NeuralNetwork>();
NeuralNetwork neuralNetworkMethods = new NeuralNetwork(0, 0, 0);
int randomInt = random.Next(101);
for (int x = 0; x < neuralNetworkArgs.Length; x++)
{
if (randomInt < percentAmountMutate)
{
List<Neuron> input = new List<Neuron>(), hidden = new List<Neuron>(), output = new List<Neuron>();
randomInt = random.Next(101);
for (int y = 0; y < neuralNetworkArgs[x].input.Length; y++)
{
if (randomInt < percentMutate)
input.Add(neuralNetworkMethods.MutateNeuron(neuralNetworkArgs[x].input[y], neuralNetworkArgs[x].hidden));
else
input.Add(neuralNetworkArgs[x].input[y]);
randomInt = random.Next(101);
}
for (int y = 0; y < neuralNetworkArgs[x].hidden.Length; y++)
{
if (randomInt < percentMutate)
hidden.Add(neuralNetworkMethods.MutateNeuron(neuralNetworkArgs[x].hidden[y], neuralNetworkArgs[x].output));
else
hidden.Add(neuralNetworkArgs[x].hidden[y]);
randomInt = random.Next(101);
}
foreach (Neuron neuron in neuralNetworkArgs[x].output)
output.Add(neuron);
neuralNetwork.Add(new NeuralNetwork(input.Count, hidden.Count, output.Count));
neuralNetwork[x].EstablishExistingNetwork(input.ToArray(), hidden.ToArray(), output.ToArray());
}
else
{
neuralNetwork.Add(neuralNetworkArgs[x]);
}
randomInt = random.Next(101);
}
return neuralNetwork.ToArray();
}