public Individ mutate(Random rand, double tau1, double tau2, FuzzySystem.FuzzyAbstract.learn_algorithm.conf.ESConfig.Type_Mutate type_mutate, double b_ro)
{
switch (type_mutate)
{
case FuzzySystem.FuzzyAbstract.learn_algorithm.conf.ESConfig.Type_Mutate.СКО:
{
hrom_vector.mutate_SKO(step_sko, rand);
for (int i = 0; i < step_sko.Count; i++)
{
step_sko[i] = step_sko[i] * Math.Exp(tau1 * GaussRandom.Random_gaussian(rand) + tau2 * GaussRandom.Random_gaussian(rand));
}
break;
}
case FuzzySystem.FuzzyAbstract.learn_algorithm.conf.ESConfig.Type_Mutate.СКО_РО:
{
List <double> Covariance_matrix_pruned = new List <double>();
for (int i = 0; i < step_sko.Count; i++) // mutate
{
step_sko[i] = step_sko[i] * Math.Exp(tau1 * GaussRandom.Random_gaussian(rand) + tau2 * GaussRandom.Random_gaussian(rand));
step_rotate[i] = step_rotate[i] + b_ro * GaussRandom.Random_gaussian(rand);
}
double avr_ro = step_rotate.Sum() / step_rotate.Count;
double avr_sko = step_sko.Sum() / step_sko.Count;
for (int i = 0; i < step_sko.Count; i++) //calc covariance_matrix_pruned
{
Covariance_matrix_pruned.Add(Math.Abs(
(step_sko[i] - avr_sko) * (step_rotate[i] - avr_ro)
)
);
}
hrom_vector.mutate_SKO_RO(Covariance_matrix_pruned, rand);
break;
}
}
return(this);
}
