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;
}
