private void UpdatePositionAndVelocity(Particle particle)
{
UpdateVelocity(particle);
UpdatePosition(particle);
}
private void UpdateVelocity(Particle particle)
{
var newVelocity = new double[_vectorSize];
Parallel.For(0, newVelocity.Length, i =>
{
CognitiveRandomizer1 = _random.NextDouble();
CognitiveRandomizer2 = _random.NextDouble();
newVelocity[i] = (InertiaWeight * particle.Properties.Velocity[i]) +
(CognitiveWeight * CognitiveRandomizer1 *
(particle.Properties.BestPosition[i] - particle.Properties.Position[i])) +
(SocialWeight * CognitiveRandomizer2 * (BestGlobalPosition[i] - particle.Properties.Position[i]));
});
Array.Copy(newVelocity, particle.Properties.Velocity, newVelocity.Length);
}
private void UpdatePosition(Particle particle)
{
var newPosition = new double[_vectorSize];
Parallel.For(0, newPosition.Length, i =>
{
newPosition[i] = particle.Properties.Position[i] + particle.Properties.Velocity[i];
if (newPosition[i] < _configuration.DimensionMinimum)
{
newPosition[i] = _configuration.DimensionMinimum;
}
if (newPosition[i] > _configuration.DimensionMaximum)
{
newPosition[i] = _configuration.DimensionMaximum;
}
});
Array.Copy(newPosition, particle.Properties.Position, newPosition.Length);
}
private void UpdateParticleError(NeuralNetworkConfiguration configuration, double[][] dataVectors, Particle particle)
{
var newError = Error(configuration, dataVectors, particle.Properties.Position);
particle.ParticleError.Error = newError;
if (newError < particle.ParticleError.BestError)
{
var bestPosition = particle.Properties.BestPosition;
Array.Copy(particle.Properties.Position, particle.Properties.BestPosition, bestPosition.Length);
particle.ParticleError.BestError = newError;
}
if (!(newError < BestGlobalError))
return;
var position = particle.Properties.Position;
Array.Copy(particle.Properties.Position, BestGlobalPosition, position.Length);
BestGlobalError = newError;
}
private void LiveOrDie(Particle particle, NeuralNetworkConfiguration configuration, double[][] dataVectors)
{
var currentLifeProbability = _random.NextDouble();
if (!(currentLifeProbability < ParticleDeathProbability))
return;
var position = particle.Properties.Position;
for (var i = 0; i < position.Length; i++)
particle.Properties.Position[i] = (_configuration.DimensionMaximum - _configuration.DimensionMinimum) * _random.NextDouble() + _configuration.DimensionMinimum;
particle.ParticleError.Error = Error(configuration, dataVectors, particle.Properties.Position);
particle.ParticleError.BestError = particle.ParticleError.Error;
Array.Copy(particle.Properties.Position, particle.Properties.BestPosition,position.Length);
if (!(particle.ParticleError.Error < BestGlobalError))
return;
BestGlobalError = particle.ParticleError.Error;
var particlePosition = particle.Properties.Position;
Array.Copy(particle.Properties.Position, BestGlobalPosition, particlePosition.Length);
}
private void CreateParticleForSwarm(NeuralNetworkConfiguration configuration, double[][] dataVectors, int i)
{
var properties = new ParticleProperties(_vectorSize);
var randomPosition = InitializeRandomPosition();
var error = Error(configuration, dataVectors, randomPosition);
var particleError = new ParticleError
{
Error = error,
BestError = error
};
var randomVelocity = InitializeRandomVelocity();
Array.Copy(randomPosition, properties.Position, randomPosition.Length);
Array.Copy(randomPosition, properties.BestPosition, randomPosition.Length);
Array.Copy(randomVelocity, properties.Velocity, randomVelocity.Length);
_swarm[i] = new Particle(particleError, properties);
}
Particle[] CreateParticles(int swarmSize)
{
Particle[] swarm = new Particle[swarmSize];
for (int i = 0; i < swarmSize; i++)
{
swarm[i] = new Particle (this);
}
return swarm;
}
