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) { }