public void CalculateWeights(BoltzmannMachine logic)
{
for (var sourceTour = 0; sourceTour < NUM_CITIES; sourceTour++)
{
for (var sourceCity = 0; sourceCity < NUM_CITIES; sourceCity++)
{
var sourceIndex = sourceTour * NUM_CITIES + sourceCity;
for (var targetTour = 0; targetTour < NUM_CITIES; targetTour++)
{
for (var targetCity = 0; targetCity < NUM_CITIES; targetCity++)
{
var targetIndex = targetTour * NUM_CITIES + targetCity;
double weight = 0;
if (sourceIndex != targetIndex)
{
var predTargetTour = targetTour == 0 ? NUM_CITIES - 1 : targetTour - 1;
var succTargetTour = targetTour == NUM_CITIES - 1 ? 0 : targetTour + 1;
if ((sourceTour == targetTour) || (sourceCity == targetCity))
{
weight = -gamma;
}
else if ((sourceTour == predTargetTour) || (sourceTour == succTargetTour))
{
weight = -distance[sourceCity][targetCity];
}
}
logic.SetWeight(sourceIndex, targetIndex, weight);
}
}
logic.Threshold[sourceIndex] = -gamma / 2;
}
}
}
public void TestPersistSerial()
{
BoltzmannMachine network = new BoltzmannMachine(4);
network.SetWeight(1, 1, 1);
network.Threshold[2] = 2;
SerializeObject.Save(SERIAL_FILENAME.ToString(), network);
BoltzmannMachine network2 = (BoltzmannMachine)SerializeObject.Load(SERIAL_FILENAME.ToString());
ValidateHopfield(network2);
}
public void TestPersistEG()
{
BoltzmannMachine network = new BoltzmannMachine(4);
network.SetWeight(1, 1, 1);
network.Threshold[2] = 2;
EncogDirectoryPersistence.SaveObject(EG_FILENAME, network);
BoltzmannMachine network2 = (BoltzmannMachine)EncogDirectoryPersistence.LoadObject(EG_FILENAME);
ValidateHopfield(network2);
}
public void CalculateWeights(BoltzmannMachine network)
{
int n1, n2, n3, n4;
int i, j;
int predN3, succN3;
double weight;
for (n1 = 0; n1 < NUM_CITIES; n1++)
{
for (n2 = 0; n2 < NUM_CITIES; n2++)
{
i = n1 * NUM_CITIES + n2;
for (n3 = 0; n3 < NUM_CITIES; n3++)
{
for (n4 = 0; n4 < NUM_CITIES; n4++)
{
j = n3 * NUM_CITIES + n4;
weight = 0;
if (i != j)
{
predN3 = (n3 == 0 ? NUM_CITIES - 1 : n3 - 1);
succN3 = (n3 == NUM_CITIES - 1 ? 0 : n3 + 1);
if ((n1 == n3) || (n2 == n4))
{
weight = -gamma;
}
else if ((n1 == predN3) || (n1 == succN3))
{
weight = -distance[n2][n4];
}
}
network.SetWeight(i, j, weight);
}
}
network.Threshold[i] = (-gamma / 2);
}
}
}