public NeuralNetwork(NeuralNetworkState savedState)
{
InputLayerSize = savedState.inputLayerSize;
HiddenLayerSize = savedState.hiddenLayerSize;
OutputLayerSize = savedState.outputLayerSize;
inputs = new double[InputLayerSize];
hiddenLayer = new Neuron[HiddenLayerSize];
for (int i = 0; i < hiddenLayer.Length; i++)
{
hiddenLayer[i] = new Neuron(savedState.hiddenLayerState[i]);
}
outputLayer = new Neuron[OutputLayerSize];
for (int i = 0; i < outputLayer.Length; i++)
{
outputLayer[i] = new Neuron(savedState.outputLayerState[i]);
}
Eta = savedState.eta;
}
private void loadPresetNeuralNetwork()
{
System.Xml.Serialization.XmlSerializer reader = new System.Xml.Serialization.XmlSerializer(typeof(NeuralNetworkState));
if (File.Exists(@"presetNN.xml"))
{
var file = new StreamReader(@"presetNN.xml");
NeuralNetworkState presetState = (NeuralNetworkState)reader.Deserialize(file);
file.Close();
PresetNeuralNetwork = new NeuralNetworkUCI(presetState);
textBoxPresetNeuralNetwork.Text =
"Preset Neural Network:\r\n" +
PresetNeuralNetwork.GetInfo() + "\r\n" +
testNeuralNetwork(PresetNeuralNetwork);
selectCharacterImage(selectedCharacterImage);
}
else
{
textBoxPresetNeuralNetwork.Text = "Could not load preset neural network. \r\nMake sure presetNN.xml exists in application folder.";
}
}
public NeuralNetworkUCI(NeuralNetworkState savedState) : base(savedState)
{
}