// виклик діалогу для збереження мережі BackPropagation у файл
private void saveFileBackProp_FileOk(object sender, CancelEventArgs e)
{
string filepath = saveFileDialog.FileName;
if (filepath == null || bpn == null)
{
return;
}
bpn.Save(filepath);
MessageBox.Show("Мережа BackPropagation збережена");
}
static void Main(string[] args)
{
string filePath = @"E:\Work\NeuralXOR.xml";
int[] layerSizes = new int[3] {
2, 2, 1
};
TransferFunction[] tFuncs = new TransferFunction[3] {
TransferFunction.None,
TransferFunction.Sigmoid,
TransferFunction.Linear
};
BackPropagationNetwork bpn = new BackPropagationNetwork(layerSizes, tFuncs);
//Example XOR-Gate
bpn.Name = "XOR-Gate";
//Define the cases
double[][] input, ouput;
input = new double[4][]; ouput = new double[4][];
for (int i = 0; i < 4; i++)
{
input[i] = new double[2]; ouput[i] = new double[1];
}
input[0][0] = 0.0; input[0][1] = 0.0; ouput[0][0] = 0.0; //false XOR false = false
input[1][0] = 1.0; input[1][1] = 0.0; ouput[1][0] = 1.0; //true XOR false = true
input[2][0] = 0.0; input[2][1] = 1.0; ouput[2][0] = 1.0; //false XOR true = true
input[3][0] = 1.0; input[3][1] = 1.0; ouput[3][0] = 0.0; //true XOR true = false
//Train the network
double error = 0.0;
int max_count = 1000, count = 0;
do
{
//Prepare for training Epoch
count++;
error = 0.0;
//Train
for (int i = 0; i < 4; i++)
{
error += bpn.Train(ref input[i], ref ouput[i], 0.15, 0.10);
}
//Show Progress
if (count % 100 == 0)
{
Console.WriteLine("Epoch {0} completed with error {1:0.0000}", count, error);
}
} while (error > 0.00001 && count <= max_count);
//Display results!
double[] networkOutput = new double[1];
for (int i = 0; i < 4; i++)
{
bpn.Run(ref input[i], out networkOutput);
Console.WriteLine("Case {3}: {0:0.0} xor {1:0.0} = {2:0.0000}", input[i][0], input[i][1], networkOutput[0], i + 1);
}
bpn.Save(filePath);
Console.ReadLine();
}
