public void mutate_all(Random rand, double tau1, double tau2, Individ.Type_Mutate type_mutate, double b_ro)
{
for (int i = 0; i < the_childs.Count; i++)
{
the_childs[i].mutate(rand, tau1, tau2, type_mutate, b_ro);
}
}
public Individ mutate(Random rand, double tau1, double tau2, Individ.Type_Mutate type_mutate, double b_ro)
{
switch (type_mutate)
{
case 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 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);
}
public override Fuzzy_system.Approx_Singletone.a_Fuzzy_System TuneUpFuzzySystem(Fuzzy_system.Approx_Singletone.a_Fuzzy_System Approximate, Abstract_learn_algorithm_conf conf)
{
count_populate = ((Es_Config)conf).Особей_в_популяции;
count_child = ((Es_Config)conf).Потомки;
count_iterate = ((Es_Config)conf).Количество_итераций;
coef_t1 = ((Es_Config)conf).Коэффициент_t1;
coef_t2 = ((Es_Config)conf).Коэффициент_t2;
param_crossover = ((Es_Config)conf).Вероятность_скрещивания;
alg_cross = ((Es_Config)conf).Алгоритм_Скрещивания;
type_init = ((Es_Config)conf).Алгоритм_Инициализации;
count_Multipoint = ((Es_Config)conf).Точек_Скрещивания;
type_mutate = ((Es_Config)conf).Алгоритм_Мутации;
b_ro = ((Es_Config)conf).Изменение_РО;
a_Fuzzy_System result = Approximate;
Population main_pop = new Population(count_populate, count_child, result.Count_Vars, result.Learn_Samples_set);
main_pop.init_first(result.Rulles_Database_Set[0], rand, type_init);
for (int i = 0; i < count_iterate; i++)
{
double inparam = 0;
switch (alg_cross)
{
case Individ.Alg_crossover.Унифицированный: inparam = param_crossover; break;
case Individ.Alg_crossover.Многоточечный: inparam = count_Multipoint; break;
}
main_pop.select_parents_and_crossover(rand, alg_cross, inparam);
main_pop.mutate_all(rand, coef_t1, coef_t2, type_mutate, b_ro);
main_pop.union_parent_and_child();
main_pop.Calc_Error(result);
main_pop.select_global();
}
result.Rulles_Database_Set[0] = main_pop.get_best_database();
GC.Collect();
return(result);
}
