public override a_Fuzzy_System Generate(a_Fuzzy_System Approximate, Abstract_generator_conf config) { type_alg = ((k_mean_rules_generator_conf)config).Алгоритм; count_rules = ((k_mean_rules_generator_conf)config).Количество_правил; type_func = ((k_mean_rules_generator_conf)config).Функция_принадлежности; nebulisation_factor = ((k_mean_rules_generator_conf)config).Экспоненциальный_вес_алгоритма; Max_iteration = ((k_mean_rules_generator_conf)config).Итераций; need_precision = ((k_mean_rules_generator_conf)config).Точность; k_mean_base K_Agl = null; switch (type_alg) { case Type_k_mean_algorithm.Gath_geva: K_Agl = new k_mean_Gath_Geva(Approximate.Learn_Samples_set, Max_iteration, need_precision, count_rules, nebulisation_factor); break; case Type_k_mean_algorithm.Gustafson_Kessel: K_Agl = new k_mean_Gustafson_kessel(Approximate.Learn_Samples_set, Max_iteration, need_precision, count_rules, nebulisation_factor); break; case Type_k_mean_algorithm.FCM: K_Agl = new k_mean_base(Approximate.Learn_Samples_set, Max_iteration, need_precision, count_rules, nebulisation_factor); break; } K_Agl.Calc(); Knowlege_base_ARules New_Rules = new Knowlege_base_ARules(); for (int i = 0; i < count_rules; i++) { int [] order_terms = new int [Approximate.Learn_Samples_set.Count_Vars]; List <Term> term_set = new List <Term>(); for (int j = 0; j < Approximate.Learn_Samples_set.Count_Vars; j++) { Term temp_term = Term.Make_Term(K_Agl.Centroid_cordinate_S[i][j], Math.Sqrt(Calc_distance_for_member_ship_function_for_Clust(i, j, K_Agl)) * 3, type_func, j); term_set.Add(temp_term); } New_Rules.constuct__and_add_the_Rule(term_set, Approximate); } a_Fuzzy_System Result = Approximate; if (Result.Rulles_Database_Set.Count > 0) { Result.Rulles_Database_Set[0] = New_Rules; } else { Result.Rulles_Database_Set.Add(New_Rules); } Result.unlaid_protection_fix(); GC.Collect(); return(Result); }
public override a_Fuzzy_System Generate(a_Fuzzy_System Approximate, Abstract_generator_conf config) { a_Fuzzy_System result = Approximate; init_everyone_with_everyone config1 = config as init_everyone_with_everyone; type_func = config1.Функция_принадлежности; count_slice_vars = config1.Количество_термов_для_каждого_признака; result.Init_Rules_everyone_with_everyone(type_func, count_slice_vars); return(result); }
abstract public a_Fuzzy_System Generate(a_Fuzzy_System Approximate, Abstract_generator_conf config);
public override c_Fuzzy_System Generate(Fuzzy_system.Class_Pittsburgh.c_Fuzzy_System Classifier, Abstract_generator_conf config) { Random rand = new Random(); c_Fuzzy_System result = Classifier; if (result.Count_Rulles_Databases == 0) { Knowlege_base_CRules temp_rules = new Knowlege_base_CRules(); result.Rulles_Database_Set.Add(temp_rules); } Type_Term_Func_Enum type_term = ((Generator_Rulles_simple_random_conf)config).Функция_принадлежности; int stable_terms = (int)((Generator_Rulles_simple_random_conf)config).Тип_Термов; int count_rules = ((Generator_Rulles_simple_random_conf)config).Количество_правил; for (int j = 0; j < count_rules; j++) { int[] order = new int[result.Count_Vars]; Type_Term_Func_Enum temp_type_term; if (stable_terms == 0) { temp_type_term = type_term; } else { temp_type_term = Generator_type_term(); } List <Term> temp_term_list = new List <Term>(); for (int k = 0; k < result.Count_Vars; k++) { double[] parametrs = new double[c_Fuzzy_System.Count_Params_For_Term(temp_type_term)]; switch (temp_type_term) { case Type_Term_Func_Enum.Треугольник: parametrs[0] = result.Learn_Samples_set.Attribute_Min(k) + rand.NextDouble() * (result.Learn_Samples_set.Attribute_Max(k) - result.Learn_Samples_set.Attribute_Min(k)); parametrs[1] = result.Learn_Samples_set.Attribute_Min(k) + rand.NextDouble() * (result.Learn_Samples_set.Attribute_Max(k) - result.Learn_Samples_set.Attribute_Min(k)); parametrs[2] = result.Learn_Samples_set.Attribute_Min(k) + rand.NextDouble() * (result.Learn_Samples_set.Attribute_Max(k) - result.Learn_Samples_set.Attribute_Min(k)); Array.Sort(parametrs); break; case Type_Term_Func_Enum.Гауссоида: parametrs[0] = result.Learn_Samples_set.Attribute_Min(k) + rand.NextDouble() * (result.Learn_Samples_set.Attribute_Max(k) - result.Learn_Samples_set.Attribute_Min(k)); parametrs[1] = (rand.NextDouble() + 0.01) * 0.5 * (result.Learn_Samples_set.Attribute_Max(k) - result.Learn_Samples_set.Attribute_Min(k)); break; case Type_Term_Func_Enum.Парабола: parametrs[0] = result.Learn_Samples_set.Attribute_Min(k) + rand.NextDouble() * (result.Learn_Samples_set.Attribute_Max(k) - result.Learn_Samples_set.Attribute_Min(k)); parametrs[1] = result.Learn_Samples_set.Attribute_Min(k) + rand.NextDouble() * (result.Learn_Samples_set.Attribute_Max(k) - result.Learn_Samples_set.Attribute_Min(k)); Array.Sort(parametrs); break; case Type_Term_Func_Enum.Трапеция: parametrs[0] = result.Learn_Samples_set.Attribute_Min(k) + rand.NextDouble() * (result.Learn_Samples_set.Attribute_Max(k) - result.Learn_Samples_set.Attribute_Min(k)); parametrs[1] = result.Learn_Samples_set.Attribute_Min(k) + rand.NextDouble() * (result.Learn_Samples_set.Attribute_Max(k) - result.Learn_Samples_set.Attribute_Min(k)); parametrs[2] = result.Learn_Samples_set.Attribute_Min(k) + rand.NextDouble() * (result.Learn_Samples_set.Attribute_Max(k) - result.Learn_Samples_set.Attribute_Min(k)); parametrs[3] = result.Learn_Samples_set.Attribute_Min(k) + rand.NextDouble() * (result.Learn_Samples_set.Attribute_Max(k) - result.Learn_Samples_set.Attribute_Min(k)); Array.Sort(parametrs); break; } Term temp_term = new Term(parametrs, temp_type_term, k); result.Rulles_Database_Set[0].Terms_Set.Add(temp_term); temp_term_list.Add(temp_term); order[k] = result.Rulles_Database_Set[0].Terms_Set.Count - 1; } string class_label = result.Nearest_Class(temp_term_list); CRule temp_Rule = new CRule(result.Rulles_Database_Set[0].Terms_Set, order, class_label, 1.0); result.Rulles_Database_Set[0].Rules_Database.Add(temp_Rule); } result.unlaid_protection_fix(); return(result); }
public void Init_Rules_everyone_with_everyone(Abstract_generator_conf conf) { }
public void Set_count_add_generator(int count_used_Algorithm) { Rules_generator_conf = new Abstract_generator_conf[count_used_Algorithm]; Rules_generator_type = new add_generator_for_Singleton[count_used_Algorithm]; }
public override a_Fuzzy_System Generate(Fuzzy_system.Approx_Singletone.a_Fuzzy_System Approximate, Abstract_generator_conf config) { Random rand = new Random(); a_Fuzzy_System result = Approximate; if (result.Count_Rulles_Databases == 0) { Knowlege_base_ARules temp_rules = new Knowlege_base_ARules(); result.Rulles_Database_Set.Add(temp_rules); } type_term = ((Generator_Rulles_simple_random_conf)config).Функция_принадлежности; stable_terms = (int)((Generator_Rulles_simple_random_conf)config).Тип_Термов; count_rules = ((Generator_Rulles_simple_random_conf)config).Количество_правил; for (int j = 0; j < count_rules; j++) { int[] order = new int[result.Count_Vars]; Type_Term_Func_Enum temp_type_term; if (stable_terms == 0) { temp_type_term = type_term; } else { temp_type_term = Generator_type_term(); } List <Term> temp_term_list = new List <Term>(); for (int k = 0; k < result.Count_Vars; k++) { double[] parametrs = new double[Member_Function.Count_Params_For_Term(temp_type_term)]; switch (temp_type_term) { case Type_Term_Func_Enum.Треугольник: parametrs[0] = result.Learn_Samples_set.Attribute_Min(k) + rand.NextDouble() * (result.Learn_Samples_set.Attribute_Max(k) - result.Learn_Samples_set.Attribute_Min(k)); parametrs[1] = result.Learn_Samples_set.Attribute_Min(k) + rand.NextDouble() * (result.Learn_Samples_set.Attribute_Max(k) - result.Learn_Samples_set.Attribute_Min(k)); parametrs[2] = result.Learn_Samples_set.Attribute_Min(k) + rand.NextDouble() * (result.Learn_Samples_set.Attribute_Max(k) - result.Learn_Samples_set.Attribute_Min(k)); Array.Sort(parametrs); break; case Type_Term_Func_Enum.Гауссоида: parametrs[0] = result.Learn_Samples_set.Attribute_Min(k) + rand.NextDouble() * (result.Learn_Samples_set.Attribute_Max(k) - result.Learn_Samples_set.Attribute_Min(k)); parametrs[1] = (rand.NextDouble() + 0.01) * 0.5 * (result.Learn_Samples_set.Attribute_Max(k) - result.Learn_Samples_set.Attribute_Min(k)); break; case Type_Term_Func_Enum.Парабола: parametrs[0] = result.Learn_Samples_set.Attribute_Min(k) + rand.NextDouble() * (result.Learn_Samples_set.Attribute_Max(k) - result.Learn_Samples_set.Attribute_Min(k)); parametrs[1] = result.Learn_Samples_set.Attribute_Min(k) + rand.NextDouble() * (result.Learn_Samples_set.Attribute_Max(k) - result.Learn_Samples_set.Attribute_Min(k)); Array.Sort(parametrs); break; case Type_Term_Func_Enum.Трапеция: parametrs[0] = result.Learn_Samples_set.Attribute_Min(k) + rand.NextDouble() * (result.Learn_Samples_set.Attribute_Max(k) - result.Learn_Samples_set.Attribute_Min(k)); parametrs[1] = result.Learn_Samples_set.Attribute_Min(k) + rand.NextDouble() * (result.Learn_Samples_set.Attribute_Max(k) - result.Learn_Samples_set.Attribute_Min(k)); parametrs[2] = result.Learn_Samples_set.Attribute_Min(k) + rand.NextDouble() * (result.Learn_Samples_set.Attribute_Max(k) - result.Learn_Samples_set.Attribute_Min(k)); parametrs[3] = result.Learn_Samples_set.Attribute_Min(k) + rand.NextDouble() * (result.Learn_Samples_set.Attribute_Max(k) - result.Learn_Samples_set.Attribute_Min(k)); Array.Sort(parametrs); break; } Term temp_term = new Term(parametrs, temp_type_term, k); result.Rulles_Database_Set[0].Terms_Set.Add(temp_term); temp_term_list.Add(temp_term); order[k] = result.Rulles_Database_Set[0].Terms_Set.Count - 1; } double approx_Value = result.Nearest_Approx(temp_term_list); ARule temp_Rule = new ARule(result.Rulles_Database_Set[0].Terms_Set, order, approx_Value); result.Rulles_Database_Set[0].Rules_Database.Add(temp_Rule); } result.unlaid_protection_fix(); GC.Collect(); return(result); }
public override a_Fuzzy_System Generate(Fuzzy_system.Approx_Singletone.a_Fuzzy_System Approximate, Abstract_generator_conf config) { start_add_rules = Approximate.Count_Rulles_Databases; a_Fuzzy_System result = Approximate; if (result.Count_Rulles_Databases == 0) { result.Init_Rules_everyone_with_everyone(config); } Request_count_rules = ((Rulles_shrink_conf)config).Нужно_Правил; max_count_rules = ((Rulles_shrink_conf)config).Максимально_Правил; count_slices = ((Rulles_shrink_conf)config).Количество_термов_для_каждого_признака; min_count_rules = ((Rulles_shrink_conf)config).Минимально_Правил; type_term = ((Rulles_shrink_conf)config).Функция_принадлежности; int count_of_swith_off = ((Rulles_shrink_conf)config).Максимально_Правил - Request_count_rules; List <byte> Varians_of_run_system = new List <byte>(); for (int i = 0; i < Approximate.Rulles_Database_Set[0].Rules_Database.Count; i++) { Varians_of_run_system.Add(1); } for (int i = 0; i < count_of_swith_off; i++) { Varians_of_run_system[i] = 0; } Generate_all_variant_in_pool(Varians_of_run_system); for (int i = 0; i < Pull_of_systems.Count; i++) { Knowlege_base_ARules temp_rules = new Knowlege_base_ARules(result.Rulles_Database_Set[0], Pull_of_systems[i]); temp_rules.trim_not_used_Terms(); result.Rulles_Database_Set.Add(temp_rules); result.unlaid_protection_fix(start_add_rules + i); errors_of_systems.Add(result.approx_Learn_Samples(start_add_rules + i)); } int best_index = errors_of_systems.IndexOf(errors_of_systems.Min()); Knowlege_base_ARules best = result.Rulles_Database_Set[start_add_rules + best_index]; result.Rulles_Database_Set.Clear(); result.Rulles_Database_Set.Add(best); Console.WriteLine(Pull_of_systems.Count()); GC.Collect(); // result.unlaid_protection_fix(); return(result); }
abstract public c_Fuzzy_System Generate(c_Fuzzy_System Classifier, Abstract_generator_conf config);
public override a_Fuzzy_System Generate(Fuzzy_system.Approx_Singletone.a_Fuzzy_System Approximate, Abstract_generator_conf config) { a_Fuzzy_System result = Approximate; if (result.Count_Rulles_Databases == 0) { result.Init_Rules_everyone_with_everyone(config); } count_shrink = ((Term_shrink_and_rotate_conf)config).Число_параметров_для_уменьшения_термов; size_shrink = ((Term_shrink_and_rotate_conf)config).Значение_уменьшения_термов; type_func = ((Term_shrink_and_rotate_conf)config).Функция_принадлежности; count_slices = ((Term_shrink_and_rotate_conf)config).Количество_термов_для_каждого_признака; List <int> Varians_of_run_system = new List <int>(); for (int i = 0; i < Approximate.Count_Vars; i++) { int count_terms_for_var = Approximate.Rulles_Database_Set[0].Terms_Set.FindAll(x => x.Number_of_Input_Var == i).Count; if (i < count_shrink) { Varians_of_run_system.Add(count_terms_for_var - size_shrink); } else { Varians_of_run_system.Add(count_terms_for_var); } } Varians_of_run_system.Sort(); Type_Term_Func_Enum type_of_term = Approximate.Rulles_Database_Set[0].Terms_Set[0].Term_Func_Type; Generate_all_variant_in_pool(Varians_of_run_system); for (int i = 0; i < Pull_of_systems.Count; i++) { Approximate.Rulles_Database_Set.Clear(); Approximate.Init_Rules_everyone_with_everyone(type_of_term, Pull_of_systems[i].ToArray()); Systems_ready_to_test.Add(Approximate.Rulles_Database_Set[0]); errors_of_systems.Add(result.approx_Learn_Samples(0)); } int best_index = errors_of_systems.IndexOf(errors_of_systems.Min()); result.Rulles_Database_Set.Clear(); result.Rulles_Database_Set.Add(Systems_ready_to_test[best_index]); Console.WriteLine(Pull_of_systems.Count()); GC.Collect(); // result.unlaid_protection_fix(); return(result); }