public static LayeredNeuralNetwork buildLayeredNetwork(LayeredNeuralNetworkBlueprint blueprint)
{
var newNetwork = new LayeredNeuralNetwork();
newNetwork.inputNeurons = new NeuralLayer(blueprint.inputNeuronAmount);
newNetwork.outputNeurons = new NeuralLayer(blueprint.outputNeuronAmount);
newNetwork.hiddenLayers = blueprint.hiddenLayersNeuronAmounts.Select(amount => new NeuralLayer(amount)).ToList();
newNetwork.neuralConnections = new List <NeuralConnectionLayer>();
if (newNetwork.hiddenLayers.Count == 0)
{
newNetwork.neuralConnections.Add(
newNetwork.inputNeurons.ConnectWith(newNetwork.outputNeurons)
);
return(newNetwork);
}
// Connect input neurons with first hidden layer
newNetwork.neuralConnections.Add(
newNetwork.inputNeurons.ConnectWith(newNetwork.hiddenLayers[0])
);
// Connect hidden layers with each other
for (int i = 0; i < newNetwork.hiddenLayers.Count - 1; i++)
{
newNetwork.neuralConnections.Add(
newNetwork.hiddenLayers[i].ConnectWith(newNetwork.hiddenLayers[i + 1])
);
}
// Connect last hidden layer with output neurons
newNetwork.neuralConnections.Add(
newNetwork.hiddenLayers[newNetwork.hiddenLayers.Count - 1].ConnectWith(newNetwork.outputNeurons)
);
return(newNetwork);
}
public static int Main()
{
var hiddenLayers = new List <int>();
var networkBlueprint = new LayeredNeuralNetworkBlueprint
{
inputNeuronAmount = 2,
outputNeuronAmount = 4,
hiddenLayersNeuronAmounts = hiddenLayers
};
var network = NeuralNetworkBuilder.buildLayeredNetwork(networkBlueprint);
var sets = new List <TrainingData>();
for (int i = 0; i < 4; i++)
{
sets.Add(new TrainingData());
}
sets[0].inputs.Add(-1);
sets[0].inputs.Add(1);
sets[0].expectedOutputs.Add(true);
sets[0].expectedOutputs.Add(false);
sets[0].expectedOutputs.Add(false);
sets[0].expectedOutputs.Add(false);
sets[1].inputs.Add(1);
sets[1].inputs.Add(1);
sets[1].expectedOutputs.Add(false);
sets[1].expectedOutputs.Add(true);
sets[1].expectedOutputs.Add(false);
sets[1].expectedOutputs.Add(false);
sets[2].inputs.Add(1);
sets[2].inputs.Add(-1);
sets[2].expectedOutputs.Add(false);
sets[2].expectedOutputs.Add(false);
sets[2].expectedOutputs.Add(true);
sets[2].expectedOutputs.Add(false);
sets[3].inputs.Add(-1);
sets[3].inputs.Add(-1);
sets[3].expectedOutputs.Add(false);
sets[3].expectedOutputs.Add(false);
sets[3].expectedOutputs.Add(false);
sets[3].expectedOutputs.Add(true);
bool makeLoop = true;
int numberOfCycles = 0;
int setNumber = 0;
int good = 0;
int all = 0;
while (good != all || all == 0)
{
numberOfCycles++;
if (makeLoop)
{
good = 0;
all = 0;
for (int i = 0; i < 10000; i++)
{
setNumber = RandGen.NextInt() % 4;
if (network.Teach(sets[setNumber].inputs, sets[setNumber].expectedOutputs))
{
good++;
}
all++;
}
}
Console.WriteLine(numberOfCycles + ". good: " + good + "/" + all);
SaveToFile(@"C:\Users\Majek\Desktop\WriteText.txt", good, all);
}
return(0);
}
