public void NetworkSetup(int inputs, int outputs) { int hiddens = (inputs + outputs) * 3 / 2; network = new BPNet(); network.CreateNet(3, inputs, hiddens, outputs); network.SetActivationFunctions(new SigmoidFunction(), new SigmoidFunction()); //Debug.Assert(network.CreateNet(3, inputs, hiddens, outputs) == 0); //Debug.Log(network.Layer.ToString()); //Debug.Assert(network.SetActivationFunctions(new TanhFunction(), new TanhFunction()) == 0); }
private void StartTrainNNButton_Click(object sender, RoutedEventArgs e) { MessageBox.Show("神经网络训练中,关闭此通知后请耐心等待!", "通知"); //训练神经网络 int hidden = Convert.ToInt32(HiddenBlock.Text); int iter_max = Convert.ToInt32(NNIterBlock.Text); BPNet bp = new BPNet("NetWeight.txt", IOFor12.XDimension, hidden, IOFor12.TDimension, iter_max); bp.TrainBPNet(IOFor12.XData, IOFor12.TData); MessageBox.Show("神经网络训练完毕!\n网络权值已保存在NetWeight.txt中!\n神经网络训练结果已保存在根目录中!" , "通知"); StartTrainNNButton.Content = "开始训练"; StartTrainNNButton.IsEnabled = true; }