質問編集履歴
4
test
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File without changes
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test
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@@ -1,599 +1 @@
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```C++
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#include <iostream>
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#include<fstream>
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#include<sstream>
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#include<cmath>
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#include<stdio.h>
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#include<stdlib.h>
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//データ数
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#define N 61
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//次元数
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#define N_d 2
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//クラス数
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#define N_c 3
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//個体群サイズ(ルール数)
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#define N_rp 16
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using namespace std;
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class Fuzzy {
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public:
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//コンストラクタ
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Fuzzy() {
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//ファジィルール初期化
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int i = 0;
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int j = 0;
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rule[0][0] = 1;
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rule[1][0] = 1;
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rule[2][0] = 1;
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rule[3][0] = 1;
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rule[4][0] = 2;
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rule[5][0] = 2;
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rule[6][0] = 2;
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rule[7][0] = 2;
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rule[8][0] = 3;
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rule[9][0] = 3;
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rule[10][0] = 3;
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rule[11][0] = 3;
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rule[12][0] = 0;
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rule[13][0] = 0;
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rule[14][0] = 0;
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rule[15][0] = 0;
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rule[0][1] = 1;
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rule[1][1] = 2;
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rule[2][1] = 3;
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rule[3][1] = 0;
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rule[4][1] = 1;
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rule[5][1] = 2;
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rule[6][1] = 3;
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rule[7][1] = 0;
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rule[8][1] = 1;
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rule[9][1] = 2;
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rule[10][1] = 3;
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rule[11][1] = 0;
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rule[12][1] = 1;
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rule[13][1] = 2;
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rule[14][1] = 3;
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rule[15][1] = 0;
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//ルール選択配列初期化
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for (int i = 0; i<N_rp; i++) {
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rule_select[i] = 1;
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rule_select_2[i] = 1;
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}
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fitness = 0;
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}
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//学習用データの読み込み
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void read_data() {
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double data1x[N][N_d];
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double x1[N]; //臨時配列(パターン１)
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double x2[N]; //臨時配列(パターン１)
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int c11[N]; //臨時配列(パターン１)
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int i = 0;
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FILE *fp1;
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errno_t error1;
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if ((error1 = fopen_s(&fp1, "kadai3_pattern1.txt", "r")) != 0) {
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printf("cannot open the file\n");
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}
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else {
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while (fscanf_s(fp1, "%lf,%lf,%d", &x1[i], &x2[i], &c11[i]) != EOF) {
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data[i][0] = x1[i];
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data[i][1] = x2[i];
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data[i][2] = (double)c11[i];
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i++;
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}
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}
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fclose(fp1);
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//データの格納終了
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}
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//適合度計算
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void calc_fit() {
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double a, tmp, fit;
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for (int h = 0; h < N_rp; h++) {
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for (int i = 1; i <= N; i++) {
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fit = 1;
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//各ルールでの各データパターンでの適合度計算
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for (int j = 0; j < N_d; j++) {
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//don't care ならメンバシップ値は1
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if ((int)rule[h][j] == 0)continue;
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a = (double)(rule[h][j] - 1) / 2;
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tmp = 1 - 2 * abs(a - data[i][j]);
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if (tmp > 0) {
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fit *= tmp;
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}
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else {
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fit = 0;
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break;
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}
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}
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rule_fit[h][i - 1] = fit;
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}
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}
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}
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//信頼度計算
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void calc_trust() {
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//適合度の和を入れる tmp2はクラスhを指すデータの適合度の和
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double tmp, tmp2;
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for (int k = 0; k < N_rp; k++) {
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231
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//クラスは3種
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for (int i = 0; i < 3; i++) {
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tmp = 0;
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tmp2 = 0;
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238
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239
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for (int j = 1; j <= N; j++) {
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240
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241
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if ((int)data[j][2] == i) {
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242
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243
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tmp2 += rule_fit[k][j - 1];
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245
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}
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246
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247
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tmp += rule_fit[k][j - 1];
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249
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}
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250
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251
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rule_class[k][i] = tmp2 / tmp;
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253
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}
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255
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}
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256
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257
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}
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258
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259
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//各ルール結論クラス決定
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260
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261
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void calc_class() {
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262
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263
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double tmp;
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264
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265
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int tmp_class;
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266
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267
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for (int i = 0; i <N_rp; i++) {
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268
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269
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tmp = rule_class[i][0];
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270
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271
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tmp_class = 0;
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272
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273
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//最も信頼度の高いクラスに決定
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274
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275
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for (int j = 1; j <3; j++) {
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276
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277
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if (tmp < rule_class[i][j]) {
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278
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279
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tmp = rule_class[i][j];
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280
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281
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tmp_class = j;
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282
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283
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}
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284
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285
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}
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286
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287
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//結論部クラス決定
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288
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289
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rule[i][2] = tmp_class;
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290
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291
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//ルール重み計算
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292
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293
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for (int j = 0; j <3; j++) {
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294
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295
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if (j != tmp_class) {
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296
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297
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tmp -= rule_class[i][j];
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298
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299
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}
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300
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301
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//ルール重みが0以下ならそのルールは不要
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302
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303
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if (tmp <= 0) {
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304
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305
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rule[i][4] = 0;
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306
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307
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break;
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308
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309
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}
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310
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311
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rule[i][3] = tmp;
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312
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313
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}
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314
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315
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}
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316
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317
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}
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318
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319
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//総ルール長とルール数の計算
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320
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321
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void count_rule() {
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322
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323
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rule_len = 0;
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324
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325
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rule_num = 0;
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326
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327
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for (int i = 0; i<N_rp; i++) {
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328
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329
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if ((int)rule[i][4] == 1 && rule_select[i] == 1) {
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330
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331
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if ((int)rule[i][0] != 0)rule_len++;
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332
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333
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rule_num++;
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334
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335
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if ((int)rule[i][1] != 0)rule_len++;
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336
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337
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}
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338
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339
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}
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340
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341
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}
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342
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-
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343
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//識別率計算
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344
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345
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void calc_ans() {
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346
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347
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double tmp;
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348
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-
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349
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//異なる結論クラスを持つが適合度とルール重みの和が等しくなった時にチェック
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350
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351
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bool check = false;
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352
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353
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//それぞれ正解した数、合計数
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354
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355
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int collect_num = 0;
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356
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357
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int sum = 0;
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358
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-
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359
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double win_tmp = 0;
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360
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361
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int win_num = 0;
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362
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363
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for (int j = 1; j <= 60; j++) {
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364
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365
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win_tmp = 0;
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366
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367
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win_num = 0;
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368
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369
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check = false;
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370
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371
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for (int i = 0; i < N_rp; i++) {
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372
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-
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373
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//勝者ルールの決定
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374
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375
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//不使用ルール
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376
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-
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377
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if ((int)rule[i][4] == 0 || rule_select[i] == 0)continue;
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378
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-
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379
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tmp = rule[i][3] * rule_fit[i][j - 1];
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380
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-
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381
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if (win_tmp < tmp) {
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382
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383
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win_tmp = tmp;
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384
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385
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win_num = i;
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386
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-
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387
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check = false;
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388
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-
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389
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-
}
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390
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-
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391
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-
else if (tmp == 0)continue;
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392
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-
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393
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else if ((win_tmp == tmp) && (rule[win_num][2] != rule[i][2])) check = true;
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394
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-
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395
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}
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396
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-
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397
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-
//勝者ルールでの識別
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398
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-
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399
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-
if (check == true)continue;
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400
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-
|
|
401
|
-
else if (data[j][2] == rule[win_num][2])collect_num++;
|
|
402
|
-
|
|
403
|
-
sum++;
|
|
404
|
-
|
|
405
|
-
}
|
|
406
|
-
|
|
407
|
-
ans_rate = collect_num / (double)sum;
|
|
408
|
-
|
|
409
|
-
}
|
|
410
|
-
|
|
411
|
-
//識別率、総ルール数、ルール長の表示
|
|
412
|
-
|
|
413
|
-
void show1() {
|
|
414
|
-
|
|
415
|
-
cout << "calc:" << ans_rate << endl;
|
|
416
|
-
|
|
417
|
-
cout << "rule_num:" << rule_num << endl;
|
|
418
|
-
|
|
419
|
-
cout << "rule_len:" << rule_len << endl;
|
|
420
|
-
|
|
421
|
-
}
|
|
422
|
-
|
|
423
|
-
//識別率、総ルール数、ルール長の表示
|
|
424
|
-
|
|
425
|
-
void show2() {
|
|
426
|
-
|
|
427
|
-
cout << "calc:" << ans_rate_2 << endl;
|
|
428
|
-
|
|
429
|
-
cout << "rule_num:" << rule_num_2 << endl;
|
|
430
|
-
|
|
431
|
-
cout << "rule_len:" << rule_len_2 << endl;
|
|
432
|
-
|
|
433
|
-
}
|
|
434
|
-
|
|
435
|
-
//ファジィルール集合選択
|
|
436
|
-
|
|
437
|
-
void create_rule(int num) {
|
|
438
|
-
|
|
439
|
-
if (num == 0) {
|
|
440
|
-
|
|
441
|
-
for (int i = 0; i < 2; i++) {
|
|
442
|
-
|
|
443
|
-
rule_select[num] = i;
|
|
444
|
-
|
|
445
|
-
//識別率の計算
|
|
446
|
-
|
|
447
|
-
calc_ans();
|
|
448
|
-
|
|
449
|
-
//ルール数と相ルール長の計算
|
|
450
|
-
|
|
451
|
-
count_rule();
|
|
452
|
-
|
|
453
|
-
//加重和適応度の計算
|
|
454
|
-
|
|
455
|
-
if ((1000 * ans_rate - rule_num - rule_len) > fitness) {
|
|
456
|
-
|
|
457
|
-
fitness = 1000 * ans_rate - rule_num - rule_len;
|
|
458
|
-
|
|
459
|
-
ans_rate_2 = ans_rate;
|
|
460
|
-
|
|
461
|
-
rule_len_2 = rule_len;
|
|
462
|
-
|
|
463
|
-
rule_num_2 = rule_num;
|
|
464
|
-
|
|
465
|
-
for (int j = 0; j<N_rp; j++) {
|
|
466
|
-
|
|
467
|
-
rule_select_2[j] = rule_select[j];
|
|
468
|
-
|
|
469
|
-
}
|
|
470
|
-
|
|
471
|
-
}
|
|
472
|
-
|
|
473
|
-
}
|
|
474
|
-
|
|
475
|
-
}
|
|
476
|
-
|
|
477
|
-
else {
|
|
478
|
-
|
|
479
|
-
for (int i = 0; i<2; i++) {
|
|
480
|
-
|
|
481
|
-
rule_select[num] = i;
|
|
482
|
-
|
|
483
|
-
create_rule(num - 1);
|
|
484
|
-
|
|
485
|
-
}
|
|
486
|
-
|
|
487
|
-
}
|
|
488
|
-
|
|
489
|
-
}
|
|
490
|
-
|
|
491
|
-
protected:
|
|
492
|
-
|
|
493
|
-
///////////////////データ読み込みに関するメンバ
|
|
494
|
-
|
|
495
|
-
//学習データ格納 要素,クラスの順 0行目は入力データの情報 1行目からデータ
|
|
496
|
-
|
|
497
|
-
double data[N][N_d + 1];
|
|
498
|
-
|
|
499
|
-
//ルール配列 条件ファジイ集合,結論クラス,ルール重み、利用bitの順 利用bitが1ならそのルールは使用しない
|
|
500
|
-
|
|
501
|
-
double rule[N_rp][5];
|
|
502
|
-
|
|
503
|
-
//各ルールの適合度計算
|
|
504
|
-
|
|
505
|
-
double rule_fit[N_rp][N];
|
|
506
|
-
|
|
507
|
-
//各ルールの信頼度計算
|
|
508
|
-
|
|
509
|
-
double rule_class[N_rp][3];
|
|
510
|
-
|
|
511
|
-
//ルール数
|
|
512
|
-
|
|
513
|
-
int rule_num;
|
|
514
|
-
|
|
515
|
-
//総ルール長
|
|
516
|
-
|
|
517
|
-
int rule_len;
|
|
518
|
-
|
|
519
|
-
//識別率
|
|
520
|
-
|
|
521
|
-
double ans_rate;
|
|
522
|
-
|
|
523
|
-
//ルール集合選択配列
|
|
524
|
-
|
|
525
|
-
int rule_select[N_rp];
|
|
526
|
-
|
|
527
|
-
//加重和適応度
|
|
528
|
-
|
|
529
|
-
double fitness;
|
|
530
|
-
|
|
531
|
-
//ルール集合選択後の結果
|
|
532
|
-
|
|
533
|
-
//ルール数
|
|
534
|
-
|
|
535
|
-
int rule_num_2;
|
|
536
|
-
|
|
537
|
-
//総ルール長
|
|
538
|
-
|
|
539
|
-
int rule_len_2;
|
|
540
|
-
|
|
541
|
-
//識別率
|
|
542
|
-
|
|
543
|
-
double ans_rate_2;
|
|
544
|
-
|
|
545
|
-
//ルール集合選択配列
|
|
546
|
-
|
|
547
|
-
int rule_select_2[N_rp];
|
|
548
|
-
|
|
549
|
-
};
|
|
550
|
-
|
|
551
|
-
int main() {
|
|
552
|
-
|
|
553
|
-
////////////////準備///////////////////////
|
|
554
|
-
|
|
555
|
-
//オブジェクト生成
|
|
556
|
-
|
|
557
|
-
Fuzzy fuzzy;
|
|
558
|
-
|
|
559
|
-
//学習データ読み込み
|
|
560
|
-
|
|
561
|
-
fuzzy.read_data();
|
|
562
|
-
|
|
563
|
-
/////////////////////学習開始/////////////////////////
|
|
564
|
-
|
|
565
|
-
////適合度計算
|
|
566
|
-
|
|
567
|
-
fuzzy.calc_fit();
|
|
568
|
-
|
|
569
|
-
////信頼度計算
|
|
570
|
-
|
|
571
|
-
fuzzy.calc_trust();
|
|
572
|
-
|
|
573
|
-
////結論部クラス決定、ルール重み計算
|
|
574
|
-
|
|
575
|
-
fuzzy.calc_class();
|
|
576
|
-
|
|
577
|
-
fuzzy.count_rule();
|
|
578
|
-
|
|
579
|
-
////////////未知パターン識別////////////////
|
|
580
|
-
|
|
581
|
-
////識別率計算
|
|
582
|
-
|
|
583
|
-
fuzzy.calc_ans();
|
|
584
|
-
|
|
585
|
-
fuzzy.show1();
|
|
586
|
-
|
|
587
|
-
////ファジィルール選択
|
|
588
|
-
|
|
589
|
-
fuzzy.create_rule(15);
|
|
590
|
-
|
|
591
|
-
fuzzy.show2();
|
|
592
|
-
|
|
593
|
-
return 0;
|
|
594
|
-
|
|
595
|
-
}
|
|
596
|
-
|
|
597
|
-
```
|
|
598
|
-
|
|
599
1
|
識別器をC++で作成しています。show1,show2関数で識別率、ルール数、総ルール長を表示するようにしています。実行結果は、show1では、順に91.667,0,0となり、show2では93.0,0,0となりました。識別率に関しては正解データと一致しました。
|
3
test
CHANGED
|
@@ -1 +1 @@
|
|
|
1
|
-
|
|
1
|
+
識別器について、精度向上
|
test
CHANGED
|
@@ -596,4 +596,4 @@
|
|
|
596
596
|
|
|
597
597
|
```
|
|
598
598
|
|
|
599
|
-
|
|
599
|
+
識別器をC++で作成しています。show1,show2関数で識別率、ルール数、総ルール長を表示するようにしています。実行結果は、show1では、順に91.667,0,0となり、show2では93.0,0,0となりました。識別率に関しては正解データと一致しました。
|
2
削除された内容の復元を行いました
test
CHANGED
|
File without changes
|
test
CHANGED
|
@@ -1 +1,599 @@
|
|
|
1
|
-
|
|
1
|
+
```C++
|
|
2
|
+
|
|
3
|
+
#include <iostream>
|
|
4
|
+
|
|
5
|
+
#include<fstream>
|
|
6
|
+
|
|
7
|
+
#include<sstream>
|
|
8
|
+
|
|
9
|
+
#include<cmath>
|
|
10
|
+
|
|
11
|
+
#include<stdio.h>
|
|
12
|
+
|
|
13
|
+
#include<stdlib.h>
|
|
14
|
+
|
|
15
|
+
//データ数
|
|
16
|
+
|
|
17
|
+
#define N 61
|
|
18
|
+
|
|
19
|
+
//次元数
|
|
20
|
+
|
|
21
|
+
#define N_d 2
|
|
22
|
+
|
|
23
|
+
//クラス数
|
|
24
|
+
|
|
25
|
+
#define N_c 3
|
|
26
|
+
|
|
27
|
+
//個体群サイズ(ルール数)
|
|
28
|
+
|
|
29
|
+
#define N_rp 16
|
|
30
|
+
|
|
31
|
+
using namespace std;
|
|
32
|
+
|
|
33
|
+
class Fuzzy {
|
|
34
|
+
|
|
35
|
+
public:
|
|
36
|
+
|
|
37
|
+
//コンストラクタ
|
|
38
|
+
|
|
39
|
+
Fuzzy() {
|
|
40
|
+
|
|
41
|
+
//ファジィルール初期化
|
|
42
|
+
|
|
43
|
+
int i = 0;
|
|
44
|
+
|
|
45
|
+
int j = 0;
|
|
46
|
+
|
|
47
|
+
rule[0][0] = 1;
|
|
48
|
+
|
|
49
|
+
rule[1][0] = 1;
|
|
50
|
+
|
|
51
|
+
rule[2][0] = 1;
|
|
52
|
+
|
|
53
|
+
rule[3][0] = 1;
|
|
54
|
+
|
|
55
|
+
rule[4][0] = 2;
|
|
56
|
+
|
|
57
|
+
rule[5][0] = 2;
|
|
58
|
+
|
|
59
|
+
rule[6][0] = 2;
|
|
60
|
+
|
|
61
|
+
rule[7][0] = 2;
|
|
62
|
+
|
|
63
|
+
rule[8][0] = 3;
|
|
64
|
+
|
|
65
|
+
rule[9][0] = 3;
|
|
66
|
+
|
|
67
|
+
rule[10][0] = 3;
|
|
68
|
+
|
|
69
|
+
rule[11][0] = 3;
|
|
70
|
+
|
|
71
|
+
rule[12][0] = 0;
|
|
72
|
+
|
|
73
|
+
rule[13][0] = 0;
|
|
74
|
+
|
|
75
|
+
rule[14][0] = 0;
|
|
76
|
+
|
|
77
|
+
rule[15][0] = 0;
|
|
78
|
+
|
|
79
|
+
rule[0][1] = 1;
|
|
80
|
+
|
|
81
|
+
rule[1][1] = 2;
|
|
82
|
+
|
|
83
|
+
rule[2][1] = 3;
|
|
84
|
+
|
|
85
|
+
rule[3][1] = 0;
|
|
86
|
+
|
|
87
|
+
rule[4][1] = 1;
|
|
88
|
+
|
|
89
|
+
rule[5][1] = 2;
|
|
90
|
+
|
|
91
|
+
rule[6][1] = 3;
|
|
92
|
+
|
|
93
|
+
rule[7][1] = 0;
|
|
94
|
+
|
|
95
|
+
rule[8][1] = 1;
|
|
96
|
+
|
|
97
|
+
rule[9][1] = 2;
|
|
98
|
+
|
|
99
|
+
rule[10][1] = 3;
|
|
100
|
+
|
|
101
|
+
rule[11][1] = 0;
|
|
102
|
+
|
|
103
|
+
rule[12][1] = 1;
|
|
104
|
+
|
|
105
|
+
rule[13][1] = 2;
|
|
106
|
+
|
|
107
|
+
rule[14][1] = 3;
|
|
108
|
+
|
|
109
|
+
rule[15][1] = 0;
|
|
110
|
+
|
|
111
|
+
//ルール選択配列初期化
|
|
112
|
+
|
|
113
|
+
for (int i = 0; i<N_rp; i++) {
|
|
114
|
+
|
|
115
|
+
rule_select[i] = 1;
|
|
116
|
+
|
|
117
|
+
rule_select_2[i] = 1;
|
|
118
|
+
|
|
119
|
+
}
|
|
120
|
+
|
|
121
|
+
fitness = 0;
|
|
122
|
+
|
|
123
|
+
}
|
|
124
|
+
|
|
125
|
+
//学習用データの読み込み
|
|
126
|
+
|
|
127
|
+
void read_data() {
|
|
128
|
+
|
|
129
|
+
|
|
130
|
+
|
|
131
|
+
double data1x[N][N_d];
|
|
132
|
+
|
|
133
|
+
double x1[N]; //臨時配列(パターン１)
|
|
134
|
+
|
|
135
|
+
double x2[N]; //臨時配列(パターン１)
|
|
136
|
+
|
|
137
|
+
int c11[N]; //臨時配列(パターン１)
|
|
138
|
+
|
|
139
|
+
int i = 0;
|
|
140
|
+
|
|
141
|
+
FILE *fp1;
|
|
142
|
+
|
|
143
|
+
errno_t error1;
|
|
144
|
+
|
|
145
|
+
if ((error1 = fopen_s(&fp1, "kadai3_pattern1.txt", "r")) != 0) {
|
|
146
|
+
|
|
147
|
+
printf("cannot open the file\n");
|
|
148
|
+
|
|
149
|
+
}
|
|
150
|
+
|
|
151
|
+
else {
|
|
152
|
+
|
|
153
|
+
while (fscanf_s(fp1, "%lf,%lf,%d", &x1[i], &x2[i], &c11[i]) != EOF) {
|
|
154
|
+
|
|
155
|
+
data[i][0] = x1[i];
|
|
156
|
+
|
|
157
|
+
data[i][1] = x2[i];
|
|
158
|
+
|
|
159
|
+
data[i][2] = (double)c11[i];
|
|
160
|
+
|
|
161
|
+
i++;
|
|
162
|
+
|
|
163
|
+
}
|
|
164
|
+
|
|
165
|
+
}
|
|
166
|
+
|
|
167
|
+
fclose(fp1);
|
|
168
|
+
|
|
169
|
+
//データの格納終了
|
|
170
|
+
|
|
171
|
+
}
|
|
172
|
+
|
|
173
|
+
//適合度計算
|
|
174
|
+
|
|
175
|
+
void calc_fit() {
|
|
176
|
+
|
|
177
|
+
double a, tmp, fit;
|
|
178
|
+
|
|
179
|
+
for (int h = 0; h < N_rp; h++) {
|
|
180
|
+
|
|
181
|
+
for (int i = 1; i <= N; i++) {
|
|
182
|
+
|
|
183
|
+
fit = 1;
|
|
184
|
+
|
|
185
|
+
//各ルールでの各データパターンでの適合度計算
|
|
186
|
+
|
|
187
|
+
for (int j = 0; j < N_d; j++) {
|
|
188
|
+
|
|
189
|
+
//don't care ならメンバシップ値は1
|
|
190
|
+
|
|
191
|
+
if ((int)rule[h][j] == 0)continue;
|
|
192
|
+
|
|
193
|
+
a = (double)(rule[h][j] - 1) / 2;
|
|
194
|
+
|
|
195
|
+
tmp = 1 - 2 * abs(a - data[i][j]);
|
|
196
|
+
|
|
197
|
+
if (tmp > 0) {
|
|
198
|
+
|
|
199
|
+
fit *= tmp;
|
|
200
|
+
|
|
201
|
+
}
|
|
202
|
+
|
|
203
|
+
else {
|
|
204
|
+
|
|
205
|
+
fit = 0;
|
|
206
|
+
|
|
207
|
+
break;
|
|
208
|
+
|
|
209
|
+
}
|
|
210
|
+
|
|
211
|
+
}
|
|
212
|
+
|
|
213
|
+
rule_fit[h][i - 1] = fit;
|
|
214
|
+
|
|
215
|
+
}
|
|
216
|
+
|
|
217
|
+
}
|
|
218
|
+
|
|
219
|
+
}
|
|
220
|
+
|
|
221
|
+
//信頼度計算
|
|
222
|
+
|
|
223
|
+
void calc_trust() {
|
|
224
|
+
|
|
225
|
+
//適合度の和を入れる tmp2はクラスhを指すデータの適合度の和
|
|
226
|
+
|
|
227
|
+
double tmp, tmp2;
|
|
228
|
+
|
|
229
|
+
for (int k = 0; k < N_rp; k++) {
|
|
230
|
+
|
|
231
|
+
//クラスは3種
|
|
232
|
+
|
|
233
|
+
for (int i = 0; i < 3; i++) {
|
|
234
|
+
|
|
235
|
+
tmp = 0;
|
|
236
|
+
|
|
237
|
+
tmp2 = 0;
|
|
238
|
+
|
|
239
|
+
for (int j = 1; j <= N; j++) {
|
|
240
|
+
|
|
241
|
+
if ((int)data[j][2] == i) {
|
|
242
|
+
|
|
243
|
+
tmp2 += rule_fit[k][j - 1];
|
|
244
|
+
|
|
245
|
+
}
|
|
246
|
+
|
|
247
|
+
tmp += rule_fit[k][j - 1];
|
|
248
|
+
|
|
249
|
+
}
|
|
250
|
+
|
|
251
|
+
rule_class[k][i] = tmp2 / tmp;
|
|
252
|
+
|
|
253
|
+
}
|
|
254
|
+
|
|
255
|
+
}
|
|
256
|
+
|
|
257
|
+
}
|
|
258
|
+
|
|
259
|
+
//各ルール結論クラス決定
|
|
260
|
+
|
|
261
|
+
void calc_class() {
|
|
262
|
+
|
|
263
|
+
double tmp;
|
|
264
|
+
|
|
265
|
+
int tmp_class;
|
|
266
|
+
|
|
267
|
+
for (int i = 0; i <N_rp; i++) {
|
|
268
|
+
|
|
269
|
+
tmp = rule_class[i][0];
|
|
270
|
+
|
|
271
|
+
tmp_class = 0;
|
|
272
|
+
|
|
273
|
+
//最も信頼度の高いクラスに決定
|
|
274
|
+
|
|
275
|
+
for (int j = 1; j <3; j++) {
|
|
276
|
+
|
|
277
|
+
if (tmp < rule_class[i][j]) {
|
|
278
|
+
|
|
279
|
+
tmp = rule_class[i][j];
|
|
280
|
+
|
|
281
|
+
tmp_class = j;
|
|
282
|
+
|
|
283
|
+
}
|
|
284
|
+
|
|
285
|
+
}
|
|
286
|
+
|
|
287
|
+
//結論部クラス決定
|
|
288
|
+
|
|
289
|
+
rule[i][2] = tmp_class;
|
|
290
|
+
|
|
291
|
+
//ルール重み計算
|
|
292
|
+
|
|
293
|
+
for (int j = 0; j <3; j++) {
|
|
294
|
+
|
|
295
|
+
if (j != tmp_class) {
|
|
296
|
+
|
|
297
|
+
tmp -= rule_class[i][j];
|
|
298
|
+
|
|
299
|
+
}
|
|
300
|
+
|
|
301
|
+
//ルール重みが0以下ならそのルールは不要
|
|
302
|
+
|
|
303
|
+
if (tmp <= 0) {
|
|
304
|
+
|
|
305
|
+
rule[i][4] = 0;
|
|
306
|
+
|
|
307
|
+
break;
|
|
308
|
+
|
|
309
|
+
}
|
|
310
|
+
|
|
311
|
+
rule[i][3] = tmp;
|
|
312
|
+
|
|
313
|
+
}
|
|
314
|
+
|
|
315
|
+
}
|
|
316
|
+
|
|
317
|
+
}
|
|
318
|
+
|
|
319
|
+
//総ルール長とルール数の計算
|
|
320
|
+
|
|
321
|
+
void count_rule() {
|
|
322
|
+
|
|
323
|
+
rule_len = 0;
|
|
324
|
+
|
|
325
|
+
rule_num = 0;
|
|
326
|
+
|
|
327
|
+
for (int i = 0; i<N_rp; i++) {
|
|
328
|
+
|
|
329
|
+
if ((int)rule[i][4] == 1 && rule_select[i] == 1) {
|
|
330
|
+
|
|
331
|
+
if ((int)rule[i][0] != 0)rule_len++;
|
|
332
|
+
|
|
333
|
+
rule_num++;
|
|
334
|
+
|
|
335
|
+
if ((int)rule[i][1] != 0)rule_len++;
|
|
336
|
+
|
|
337
|
+
}
|
|
338
|
+
|
|
339
|
+
}
|
|
340
|
+
|
|
341
|
+
}
|
|
342
|
+
|
|
343
|
+
//識別率計算
|
|
344
|
+
|
|
345
|
+
void calc_ans() {
|
|
346
|
+
|
|
347
|
+
double tmp;
|
|
348
|
+
|
|
349
|
+
//異なる結論クラスを持つが適合度とルール重みの和が等しくなった時にチェック
|
|
350
|
+
|
|
351
|
+
bool check = false;
|
|
352
|
+
|
|
353
|
+
//それぞれ正解した数、合計数
|
|
354
|
+
|
|
355
|
+
int collect_num = 0;
|
|
356
|
+
|
|
357
|
+
int sum = 0;
|
|
358
|
+
|
|
359
|
+
double win_tmp = 0;
|
|
360
|
+
|
|
361
|
+
int win_num = 0;
|
|
362
|
+
|
|
363
|
+
for (int j = 1; j <= 60; j++) {
|
|
364
|
+
|
|
365
|
+
win_tmp = 0;
|
|
366
|
+
|
|
367
|
+
win_num = 0;
|
|
368
|
+
|
|
369
|
+
check = false;
|
|
370
|
+
|
|
371
|
+
for (int i = 0; i < N_rp; i++) {
|
|
372
|
+
|
|
373
|
+
//勝者ルールの決定
|
|
374
|
+
|
|
375
|
+
//不使用ルール
|
|
376
|
+
|
|
377
|
+
if ((int)rule[i][4] == 0 || rule_select[i] == 0)continue;
|
|
378
|
+
|
|
379
|
+
tmp = rule[i][3] * rule_fit[i][j - 1];
|
|
380
|
+
|
|
381
|
+
if (win_tmp < tmp) {
|
|
382
|
+
|
|
383
|
+
win_tmp = tmp;
|
|
384
|
+
|
|
385
|
+
win_num = i;
|
|
386
|
+
|
|
387
|
+
check = false;
|
|
388
|
+
|
|
389
|
+
}
|
|
390
|
+
|
|
391
|
+
else if (tmp == 0)continue;
|
|
392
|
+
|
|
393
|
+
else if ((win_tmp == tmp) && (rule[win_num][2] != rule[i][2])) check = true;
|
|
394
|
+
|
|
395
|
+
}
|
|
396
|
+
|
|
397
|
+
//勝者ルールでの識別
|
|
398
|
+
|
|
399
|
+
if (check == true)continue;
|
|
400
|
+
|
|
401
|
+
else if (data[j][2] == rule[win_num][2])collect_num++;
|
|
402
|
+
|
|
403
|
+
sum++;
|
|
404
|
+
|
|
405
|
+
}
|
|
406
|
+
|
|
407
|
+
ans_rate = collect_num / (double)sum;
|
|
408
|
+
|
|
409
|
+
}
|
|
410
|
+
|
|
411
|
+
//識別率、総ルール数、ルール長の表示
|
|
412
|
+
|
|
413
|
+
void show1() {
|
|
414
|
+
|
|
415
|
+
cout << "calc:" << ans_rate << endl;
|
|
416
|
+
|
|
417
|
+
cout << "rule_num:" << rule_num << endl;
|
|
418
|
+
|
|
419
|
+
cout << "rule_len:" << rule_len << endl;
|
|
420
|
+
|
|
421
|
+
}
|
|
422
|
+
|
|
423
|
+
//識別率、総ルール数、ルール長の表示
|
|
424
|
+
|
|
425
|
+
void show2() {
|
|
426
|
+
|
|
427
|
+
cout << "calc:" << ans_rate_2 << endl;
|
|
428
|
+
|
|
429
|
+
cout << "rule_num:" << rule_num_2 << endl;
|
|
430
|
+
|
|
431
|
+
cout << "rule_len:" << rule_len_2 << endl;
|
|
432
|
+
|
|
433
|
+
}
|
|
434
|
+
|
|
435
|
+
//ファジィルール集合選択
|
|
436
|
+
|
|
437
|
+
void create_rule(int num) {
|
|
438
|
+
|
|
439
|
+
if (num == 0) {
|
|
440
|
+
|
|
441
|
+
for (int i = 0; i < 2; i++) {
|
|
442
|
+
|
|
443
|
+
rule_select[num] = i;
|
|
444
|
+
|
|
445
|
+
//識別率の計算
|
|
446
|
+
|
|
447
|
+
calc_ans();
|
|
448
|
+
|
|
449
|
+
//ルール数と相ルール長の計算
|
|
450
|
+
|
|
451
|
+
count_rule();
|
|
452
|
+
|
|
453
|
+
//加重和適応度の計算
|
|
454
|
+
|
|
455
|
+
if ((1000 * ans_rate - rule_num - rule_len) > fitness) {
|
|
456
|
+
|
|
457
|
+
fitness = 1000 * ans_rate - rule_num - rule_len;
|
|
458
|
+
|
|
459
|
+
ans_rate_2 = ans_rate;
|
|
460
|
+
|
|
461
|
+
rule_len_2 = rule_len;
|
|
462
|
+
|
|
463
|
+
rule_num_2 = rule_num;
|
|
464
|
+
|
|
465
|
+
for (int j = 0; j<N_rp; j++) {
|
|
466
|
+
|
|
467
|
+
rule_select_2[j] = rule_select[j];
|
|
468
|
+
|
|
469
|
+
}
|
|
470
|
+
|
|
471
|
+
}
|
|
472
|
+
|
|
473
|
+
}
|
|
474
|
+
|
|
475
|
+
}
|
|
476
|
+
|
|
477
|
+
else {
|
|
478
|
+
|
|
479
|
+
for (int i = 0; i<2; i++) {
|
|
480
|
+
|
|
481
|
+
rule_select[num] = i;
|
|
482
|
+
|
|
483
|
+
create_rule(num - 1);
|
|
484
|
+
|
|
485
|
+
}
|
|
486
|
+
|
|
487
|
+
}
|
|
488
|
+
|
|
489
|
+
}
|
|
490
|
+
|
|
491
|
+
protected:
|
|
492
|
+
|
|
493
|
+
///////////////////データ読み込みに関するメンバ
|
|
494
|
+
|
|
495
|
+
//学習データ格納 要素,クラスの順 0行目は入力データの情報 1行目からデータ
|
|
496
|
+
|
|
497
|
+
double data[N][N_d + 1];
|
|
498
|
+
|
|
499
|
+
//ルール配列 条件ファジイ集合,結論クラス,ルール重み、利用bitの順 利用bitが1ならそのルールは使用しない
|
|
500
|
+
|
|
501
|
+
double rule[N_rp][5];
|
|
502
|
+
|
|
503
|
+
//各ルールの適合度計算
|
|
504
|
+
|
|
505
|
+
double rule_fit[N_rp][N];
|
|
506
|
+
|
|
507
|
+
//各ルールの信頼度計算
|
|
508
|
+
|
|
509
|
+
double rule_class[N_rp][3];
|
|
510
|
+
|
|
511
|
+
//ルール数
|
|
512
|
+
|
|
513
|
+
int rule_num;
|
|
514
|
+
|
|
515
|
+
//総ルール長
|
|
516
|
+
|
|
517
|
+
int rule_len;
|
|
518
|
+
|
|
519
|
+
//識別率
|
|
520
|
+
|
|
521
|
+
double ans_rate;
|
|
522
|
+
|
|
523
|
+
//ルール集合選択配列
|
|
524
|
+
|
|
525
|
+
int rule_select[N_rp];
|
|
526
|
+
|
|
527
|
+
//加重和適応度
|
|
528
|
+
|
|
529
|
+
double fitness;
|
|
530
|
+
|
|
531
|
+
//ルール集合選択後の結果
|
|
532
|
+
|
|
533
|
+
//ルール数
|
|
534
|
+
|
|
535
|
+
int rule_num_2;
|
|
536
|
+
|
|
537
|
+
//総ルール長
|
|
538
|
+
|
|
539
|
+
int rule_len_2;
|
|
540
|
+
|
|
541
|
+
//識別率
|
|
542
|
+
|
|
543
|
+
double ans_rate_2;
|
|
544
|
+
|
|
545
|
+
//ルール集合選択配列
|
|
546
|
+
|
|
547
|
+
int rule_select_2[N_rp];
|
|
548
|
+
|
|
549
|
+
};
|
|
550
|
+
|
|
551
|
+
int main() {
|
|
552
|
+
|
|
553
|
+
////////////////準備///////////////////////
|
|
554
|
+
|
|
555
|
+
//オブジェクト生成
|
|
556
|
+
|
|
557
|
+
Fuzzy fuzzy;
|
|
558
|
+
|
|
559
|
+
//学習データ読み込み
|
|
560
|
+
|
|
561
|
+
fuzzy.read_data();
|
|
562
|
+
|
|
563
|
+
/////////////////////学習開始/////////////////////////
|
|
564
|
+
|
|
565
|
+
////適合度計算
|
|
566
|
+
|
|
567
|
+
fuzzy.calc_fit();
|
|
568
|
+
|
|
569
|
+
////信頼度計算
|
|
570
|
+
|
|
571
|
+
fuzzy.calc_trust();
|
|
572
|
+
|
|
573
|
+
////結論部クラス決定、ルール重み計算
|
|
574
|
+
|
|
575
|
+
fuzzy.calc_class();
|
|
576
|
+
|
|
577
|
+
fuzzy.count_rule();
|
|
578
|
+
|
|
579
|
+
////////////未知パターン識別////////////////
|
|
580
|
+
|
|
581
|
+
////識別率計算
|
|
582
|
+
|
|
583
|
+
fuzzy.calc_ans();
|
|
584
|
+
|
|
585
|
+
fuzzy.show1();
|
|
586
|
+
|
|
587
|
+
////ファジィルール選択
|
|
588
|
+
|
|
589
|
+
fuzzy.create_rule(15);
|
|
590
|
+
|
|
591
|
+
fuzzy.show2();
|
|
592
|
+
|
|
593
|
+
return 0;
|
|
594
|
+
|
|
595
|
+
}
|
|
596
|
+
|
|
597
|
+
```
|
|
598
|
+
|
|
599
|
+
ファジィ識別器をC++で作成しています。show1,show2関数で識別率、ルール数、総ルール長を表示するようにしています。実行結果は、show1では、順に91.667,0,0となり、show2では93.0,0,0となりました。識別率に関しては正解データと一致しました。ただ、ルール数と総ルール長はshow1に関しては13,22で、show2に関しては5,8が正解となります。どこで間違っているのかがよく分からないのでよろしければ教えてください。
|
1
test
CHANGED
|
File without changes
|
test
CHANGED
|
@@ -1,709 +1 @@
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#include <iostream>
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#include<fstream>
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#include<sstream>
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#include<cmath>
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12
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13
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#include<stdio.h>
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#include<stdlib.h>
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16
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17
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18
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19
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//データ数
|
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20
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-
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21
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#define N 61
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22
|
-
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23
|
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//次元数
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24
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25
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#define N_d 2
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26
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27
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//クラス数
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28
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-
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|
29
|
-
#define N_c 3
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|
30
|
-
|
|
31
|
-
//個体群サイズ(ルール数)
|
|
32
|
-
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33
|
-
#define N_rp 16
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34
|
-
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35
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36
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37
|
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using namespace std;
|
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38
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39
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|
40
|
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41
|
-
|
|
42
|
-
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|
43
|
-
class Fuzzy {
|
|
44
|
-
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|
45
|
-
public:
|
|
46
|
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|
|
47
|
-
//コンストラクタ
|
|
48
|
-
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|
49
|
-
Fuzzy() {
|
|
50
|
-
|
|
51
|
-
|
|
52
|
-
|
|
53
|
-
//ファジィルール初期化
|
|
54
|
-
|
|
55
|
-
int i = 0;
|
|
56
|
-
|
|
57
|
-
int j = 0;
|
|
58
|
-
|
|
59
|
-
rule[0][0] = 1;
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|
60
|
-
|
|
61
|
-
rule[1][0] = 1;
|
|
62
|
-
|
|
63
|
-
rule[2][0] = 1;
|
|
64
|
-
|
|
65
|
-
rule[3][0] = 1;
|
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66
|
-
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|
67
|
-
rule[4][0] = 2;
|
|
68
|
-
|
|
69
|
-
rule[5][0] = 2;
|
|
70
|
-
|
|
71
|
-
rule[6][0] = 2;
|
|
72
|
-
|
|
73
|
-
rule[7][0] = 2;
|
|
74
|
-
|
|
75
|
-
rule[8][0] = 3;
|
|
76
|
-
|
|
77
|
-
rule[9][0] = 3;
|
|
78
|
-
|
|
79
|
-
rule[10][0] = 3;
|
|
80
|
-
|
|
81
|
-
rule[11][0] = 3;
|
|
82
|
-
|
|
83
|
-
rule[12][0] = 0;
|
|
84
|
-
|
|
85
|
-
rule[13][0] = 0;
|
|
86
|
-
|
|
87
|
-
rule[14][0] = 0;
|
|
88
|
-
|
|
89
|
-
rule[15][0] = 0;
|
|
90
|
-
|
|
91
|
-
rule[0][1] = 1;
|
|
92
|
-
|
|
93
|
-
rule[1][1] = 2;
|
|
94
|
-
|
|
95
|
-
rule[2][1] = 3;
|
|
96
|
-
|
|
97
|
-
rule[3][1] = 0;
|
|
98
|
-
|
|
99
|
-
rule[4][1] = 1;
|
|
100
|
-
|
|
101
|
-
rule[5][1] = 2;
|
|
102
|
-
|
|
103
|
-
rule[6][1] = 3;
|
|
104
|
-
|
|
105
|
-
rule[7][1] = 0;
|
|
106
|
-
|
|
107
|
-
rule[8][1] = 1;
|
|
108
|
-
|
|
109
|
-
rule[9][1] = 2;
|
|
110
|
-
|
|
111
|
-
rule[10][1] = 3;
|
|
112
|
-
|
|
113
|
-
rule[11][1] = 0;
|
|
114
|
-
|
|
115
|
-
rule[12][1] = 1;
|
|
116
|
-
|
|
117
|
-
rule[13][1] = 2;
|
|
118
|
-
|
|
119
|
-
rule[14][1] = 3;
|
|
120
|
-
|
|
121
|
-
rule[15][1] = 0;
|
|
122
|
-
|
|
123
|
-
|
|
124
|
-
|
|
125
|
-
//ルール選択配列初期化
|
|
126
|
-
|
|
127
|
-
for (int i = 0; i<N_rp; i++) {
|
|
128
|
-
|
|
129
|
-
rule_select[i] = 1;
|
|
130
|
-
|
|
131
|
-
rule_select_2[i] = 1;
|
|
132
|
-
|
|
133
|
-
}
|
|
134
|
-
|
|
135
|
-
fitness = 0;
|
|
136
|
-
|
|
137
|
-
}
|
|
138
|
-
|
|
139
|
-
|
|
140
|
-
|
|
141
|
-
//学習用データの読み込み
|
|
142
|
-
|
|
143
|
-
void read_data() {
|
|
144
|
-
|
|
145
|
-
|
|
146
|
-
|
|
147
|
-
double data1x[N][N_d];
|
|
148
|
-
|
|
149
|
-
double x1[N]; //臨時配列(パターン１)
|
|
150
|
-
|
|
151
|
-
double x2[N]; //臨時配列(パターン１)
|
|
152
|
-
|
|
153
|
-
int c11[N]; //臨時配列(パターン１)
|
|
154
|
-
|
|
155
|
-
int i = 0;
|
|
156
|
-
|
|
157
|
-
|
|
158
|
-
|
|
159
|
-
FILE *fp1;
|
|
160
|
-
|
|
161
|
-
errno_t error1;
|
|
162
|
-
|
|
163
|
-
|
|
164
|
-
|
|
165
|
-
if ((error1 = fopen_s(&fp1, "kadai3_pattern1.txt", "r")) != 0) {
|
|
166
|
-
|
|
167
|
-
printf("cannot open the file\n");
|
|
168
|
-
|
|
169
|
-
}
|
|
170
|
-
|
|
171
|
-
else {
|
|
172
|
-
|
|
173
|
-
while (fscanf_s(fp1, "%lf,%lf,%d", &x1[i], &x2[i], &c11[i]) != EOF) {
|
|
174
|
-
|
|
175
|
-
data[i][0] = x1[i];
|
|
176
|
-
|
|
177
|
-
data[i][1] = x2[i];
|
|
178
|
-
|
|
179
|
-
data[i][2] = (double)c11[i];
|
|
180
|
-
|
|
181
|
-
i++;
|
|
182
|
-
|
|
183
|
-
}
|
|
184
|
-
|
|
185
|
-
}
|
|
186
|
-
|
|
187
|
-
|
|
188
|
-
|
|
189
|
-
fclose(fp1);
|
|
190
|
-
|
|
191
|
-
//データの格納終了
|
|
192
|
-
|
|
193
|
-
|
|
194
|
-
|
|
195
|
-
|
|
196
|
-
|
|
197
|
-
}
|
|
198
|
-
|
|
199
|
-
|
|
200
|
-
|
|
201
|
-
//適合度計算
|
|
202
|
-
|
|
203
|
-
void calc_fit() {
|
|
204
|
-
|
|
205
|
-
double a, tmp, fit;
|
|
206
|
-
|
|
207
|
-
for (int h = 0; h < N_rp; h++) {
|
|
208
|
-
|
|
209
|
-
for (int i = 1; i <= N; i++) {
|
|
210
|
-
|
|
211
|
-
fit = 1;
|
|
212
|
-
|
|
213
|
-
//各ルールでの各データパターンでの適合度計算
|
|
214
|
-
|
|
215
|
-
for (int j = 0; j < N_d; j++) {
|
|
216
|
-
|
|
217
|
-
//don't care ならメンバシップ値は1
|
|
218
|
-
|
|
219
|
-
if ((int)rule[h][j] == 0)continue;
|
|
220
|
-
|
|
221
|
-
a = (double)(rule[h][j] - 1) / 2;
|
|
222
|
-
|
|
223
|
-
tmp = 1 - 2 * abs(a - data[i][j]);
|
|
224
|
-
|
|
225
|
-
if (tmp > 0) {
|
|
226
|
-
|
|
227
|
-
fit *= tmp;
|
|
228
|
-
|
|
229
|
-
}
|
|
230
|
-
|
|
231
|
-
else {
|
|
232
|
-
|
|
233
|
-
fit = 0;
|
|
234
|
-
|
|
235
|
-
break;
|
|
236
|
-
|
|
237
|
-
}
|
|
238
|
-
|
|
239
|
-
}
|
|
240
|
-
|
|
241
|
-
rule_fit[h][i - 1] = fit;
|
|
242
|
-
|
|
243
|
-
|
|
244
|
-
|
|
245
|
-
}
|
|
246
|
-
|
|
247
|
-
}
|
|
248
|
-
|
|
249
|
-
}
|
|
250
|
-
|
|
251
|
-
|
|
252
|
-
|
|
253
|
-
//信頼度計算
|
|
254
|
-
|
|
255
|
-
void calc_trust() {
|
|
256
|
-
|
|
257
|
-
//適合度の和を入れる tmp2はクラスhを指すデータの適合度の和
|
|
258
|
-
|
|
259
|
-
double tmp, tmp2;
|
|
260
|
-
|
|
261
|
-
for (int k = 0; k < N_rp; k++) {
|
|
262
|
-
|
|
263
|
-
//クラスは3種
|
|
264
|
-
|
|
265
|
-
for (int i = 0; i < 3; i++) {
|
|
266
|
-
|
|
267
|
-
tmp = 0;
|
|
268
|
-
|
|
269
|
-
tmp2 = 0;
|
|
270
|
-
|
|
271
|
-
for (int j = 1; j <= N; j++) {
|
|
272
|
-
|
|
273
|
-
|
|
274
|
-
|
|
275
|
-
if ((int)data[j][2] == i) {
|
|
276
|
-
|
|
277
|
-
tmp2 += rule_fit[k][j - 1];
|
|
278
|
-
|
|
279
|
-
}
|
|
280
|
-
|
|
281
|
-
tmp += rule_fit[k][j - 1];
|
|
282
|
-
|
|
283
|
-
}
|
|
284
|
-
|
|
285
|
-
rule_class[k][i] = tmp2 / tmp;
|
|
286
|
-
|
|
287
|
-
}
|
|
288
|
-
|
|
289
|
-
}
|
|
290
|
-
|
|
291
|
-
}
|
|
292
|
-
|
|
293
|
-
|
|
294
|
-
|
|
295
|
-
//各ルール結論クラス決定
|
|
296
|
-
|
|
297
|
-
void calc_class() {
|
|
298
|
-
|
|
299
|
-
double tmp;
|
|
300
|
-
|
|
301
|
-
int tmp_class;
|
|
302
|
-
|
|
303
|
-
for (int i = 0; i <N_rp; i++) {
|
|
304
|
-
|
|
305
|
-
tmp = rule_class[i][0];
|
|
306
|
-
|
|
307
|
-
tmp_class = 0;
|
|
308
|
-
|
|
309
|
-
//最も信頼度の高いクラスに決定
|
|
310
|
-
|
|
311
|
-
for (int j = 1; j <3; j++) {
|
|
312
|
-
|
|
313
|
-
if (tmp < rule_class[i][j]) {
|
|
314
|
-
|
|
315
|
-
tmp = rule_class[i][j];
|
|
316
|
-
|
|
317
|
-
tmp_class = j;
|
|
318
|
-
|
|
319
|
-
}
|
|
320
|
-
|
|
321
|
-
}
|
|
322
|
-
|
|
323
|
-
//結論部クラス決定
|
|
324
|
-
|
|
325
|
-
rule[i][2] = tmp_class;
|
|
326
|
-
|
|
327
|
-
//ルール重み計算
|
|
328
|
-
|
|
329
|
-
for (int j = 0; j <3; j++) {
|
|
330
|
-
|
|
331
|
-
if (j != tmp_class) {
|
|
332
|
-
|
|
333
|
-
tmp -= rule_class[i][j];
|
|
334
|
-
|
|
335
|
-
}
|
|
336
|
-
|
|
337
|
-
//ルール重みが0以下ならそのルールは不要
|
|
338
|
-
|
|
339
|
-
if (tmp <= 0) {
|
|
340
|
-
|
|
341
|
-
rule[i][4] = 0;
|
|
342
|
-
|
|
343
|
-
break;
|
|
344
|
-
|
|
345
|
-
}
|
|
346
|
-
|
|
347
|
-
rule[i][3] = tmp;
|
|
348
|
-
|
|
349
|
-
}
|
|
350
|
-
|
|
351
|
-
}
|
|
352
|
-
|
|
353
|
-
}
|
|
354
|
-
|
|
355
|
-
|
|
356
|
-
|
|
357
|
-
|
|
358
|
-
|
|
359
|
-
//総ルール長とルール数の計算
|
|
360
|
-
|
|
361
|
-
void count_rule() {
|
|
362
|
-
|
|
363
|
-
rule_len = 0;
|
|
364
|
-
|
|
365
|
-
rule_num = 0;
|
|
366
|
-
|
|
367
|
-
for (int i = 0; i<N_rp; i++) {
|
|
368
|
-
|
|
369
|
-
if ((int)rule[i][4] == 1 && rule_select[i] == 1) {
|
|
370
|
-
|
|
371
|
-
|
|
372
|
-
|
|
373
|
-
if ((int)rule[i][0] != 0)rule_len++;
|
|
374
|
-
|
|
375
|
-
rule_num++;
|
|
376
|
-
|
|
377
|
-
if ((int)rule[i][1] != 0)rule_len++;
|
|
378
|
-
|
|
379
|
-
}
|
|
380
|
-
|
|
381
|
-
}
|
|
382
|
-
|
|
383
|
-
}
|
|
384
|
-
|
|
385
|
-
|
|
386
|
-
|
|
387
|
-
//識別率計算
|
|
388
|
-
|
|
389
|
-
void calc_ans() {
|
|
390
|
-
|
|
391
|
-
double tmp;
|
|
392
|
-
|
|
393
|
-
//異なる結論クラスを持つが適合度とルール重みの和が等しくなった時にチェック
|
|
394
|
-
|
|
395
|
-
bool check = false;
|
|
396
|
-
|
|
397
|
-
//それぞれ正解した数、合計数
|
|
398
|
-
|
|
399
|
-
int collect_num = 0;
|
|
400
|
-
|
|
401
|
-
int sum = 0;
|
|
402
|
-
|
|
403
|
-
double win_tmp = 0;
|
|
404
|
-
|
|
405
|
-
int win_num = 0;
|
|
406
|
-
|
|
407
|
-
for (int j = 1; j <= 60; j++) {
|
|
408
|
-
|
|
409
|
-
win_tmp = 0;
|
|
410
|
-
|
|
411
|
-
win_num = 0;
|
|
412
|
-
|
|
413
|
-
check = false;
|
|
414
|
-
|
|
415
|
-
for (int i = 0; i < N_rp; i++) {
|
|
416
|
-
|
|
417
|
-
|
|
418
|
-
|
|
419
|
-
//勝者ルールの決定
|
|
420
|
-
|
|
421
|
-
|
|
422
|
-
|
|
423
|
-
//不使用ルール
|
|
424
|
-
|
|
425
|
-
if ((int)rule[i][4] == 0 || rule_select[i] == 0)continue;
|
|
426
|
-
|
|
427
|
-
|
|
428
|
-
|
|
429
|
-
|
|
430
|
-
|
|
431
|
-
tmp = rule[i][3] * rule_fit[i][j - 1];
|
|
432
|
-
|
|
433
|
-
if (win_tmp < tmp) {
|
|
434
|
-
|
|
435
|
-
win_tmp = tmp;
|
|
436
|
-
|
|
437
|
-
win_num = i;
|
|
438
|
-
|
|
439
|
-
check = false;
|
|
440
|
-
|
|
441
|
-
}
|
|
442
|
-
|
|
443
|
-
else if (tmp == 0)continue;
|
|
444
|
-
|
|
445
|
-
else if ((win_tmp == tmp) && (rule[win_num][2] != rule[i][2])) check = true;
|
|
446
|
-
|
|
447
|
-
}
|
|
448
|
-
|
|
449
|
-
//勝者ルールでの識別
|
|
450
|
-
|
|
451
|
-
if (check == true)continue;
|
|
452
|
-
|
|
453
|
-
else if (data[j][2] == rule[win_num][2])collect_num++;
|
|
454
|
-
|
|
455
|
-
sum++;
|
|
456
|
-
|
|
457
|
-
}
|
|
458
|
-
|
|
459
|
-
ans_rate = collect_num / (double)sum;
|
|
460
|
-
|
|
461
|
-
|
|
462
|
-
|
|
463
|
-
}
|
|
464
|
-
|
|
465
|
-
|
|
466
|
-
|
|
467
|
-
//識別率、総ルール数、ルール長の表示
|
|
468
|
-
|
|
469
|
-
void show1() {
|
|
470
|
-
|
|
471
|
-
cout << "calc:" << ans_rate << endl;
|
|
472
|
-
|
|
473
|
-
cout << "rule_num:" << rule_num << endl;
|
|
474
|
-
|
|
475
|
-
cout << "rule_len:" << rule_len << endl;
|
|
476
|
-
|
|
477
|
-
}
|
|
478
|
-
|
|
479
|
-
|
|
480
|
-
|
|
481
|
-
//識別率、総ルール数、ルール長の表示
|
|
482
|
-
|
|
483
|
-
void show2() {
|
|
484
|
-
|
|
485
|
-
cout << "calc:" << ans_rate_2 << endl;
|
|
486
|
-
|
|
487
|
-
cout << "rule_num:" << rule_num_2 << endl;
|
|
488
|
-
|
|
489
|
-
cout << "rule_len:" << rule_len_2 << endl;
|
|
490
|
-
|
|
491
|
-
}
|
|
492
|
-
|
|
493
|
-
|
|
494
|
-
|
|
495
|
-
//ファジィルール集合選択
|
|
496
|
-
|
|
497
|
-
void create_rule(int num) {
|
|
498
|
-
|
|
499
|
-
if (num == 0) {
|
|
500
|
-
|
|
501
|
-
for (int i = 0; i < 2; i++) {
|
|
502
|
-
|
|
503
|
-
rule_select[num] = i;
|
|
504
|
-
|
|
505
|
-
//識別率の計算
|
|
506
|
-
|
|
507
|
-
calc_ans();
|
|
508
|
-
|
|
509
|
-
//ルール数と相ルール長の計算
|
|
510
|
-
|
|
511
|
-
count_rule();
|
|
512
|
-
|
|
513
|
-
//加重和適応度の計算
|
|
514
|
-
|
|
515
|
-
if ((1000 * ans_rate - rule_num - rule_len) > fitness) {
|
|
516
|
-
|
|
517
|
-
fitness = 1000 * ans_rate - rule_num - rule_len;
|
|
518
|
-
|
|
519
|
-
ans_rate_2 = ans_rate;
|
|
520
|
-
|
|
521
|
-
rule_len_2 = rule_len;
|
|
522
|
-
|
|
523
|
-
rule_num_2 = rule_num;
|
|
524
|
-
|
|
525
|
-
for (int j = 0; j<N_rp; j++) {
|
|
526
|
-
|
|
527
|
-
rule_select_2[j] = rule_select[j];
|
|
528
|
-
|
|
529
|
-
}
|
|
530
|
-
|
|
531
|
-
}
|
|
532
|
-
|
|
533
|
-
}
|
|
534
|
-
|
|
535
|
-
}
|
|
536
|
-
|
|
537
|
-
else {
|
|
538
|
-
|
|
539
|
-
for (int i = 0; i<2; i++) {
|
|
540
|
-
|
|
541
|
-
rule_select[num] = i;
|
|
542
|
-
|
|
543
|
-
create_rule(num - 1);
|
|
544
|
-
|
|
545
|
-
}
|
|
546
|
-
|
|
547
|
-
|
|
548
|
-
|
|
549
|
-
}
|
|
550
|
-
|
|
551
|
-
}
|
|
552
|
-
|
|
553
|
-
|
|
554
|
-
|
|
555
|
-
|
|
556
|
-
|
|
557
|
-
protected:
|
|
558
|
-
|
|
559
|
-
///////////////////データ読み込みに関するメンバ
|
|
560
|
-
|
|
561
|
-
|
|
562
|
-
|
|
563
|
-
//学習データ格納 要素,クラスの順 0行目は入力データの情報 1行目からデータ
|
|
564
|
-
|
|
565
|
-
double data[N][N_d + 1];
|
|
566
|
-
|
|
567
|
-
|
|
568
|
-
|
|
569
|
-
|
|
570
|
-
|
|
571
|
-
|
|
572
|
-
|
|
573
|
-
|
|
574
|
-
|
|
575
|
-
//ルール配列 条件ファジイ集合,結論クラス,ルール重み、利用bitの順 利用bitが1ならそのルールは使用しない
|
|
576
|
-
|
|
577
|
-
double rule[N_rp][5];
|
|
578
|
-
|
|
579
|
-
//各ルールの適合度計算
|
|
580
|
-
|
|
581
|
-
double rule_fit[N_rp][N];
|
|
582
|
-
|
|
583
|
-
//各ルールの信頼度計算
|
|
584
|
-
|
|
585
|
-
double rule_class[N_rp][3];
|
|
586
|
-
|
|
587
|
-
//ルール数
|
|
588
|
-
|
|
589
|
-
int rule_num;
|
|
590
|
-
|
|
591
|
-
//総ルール長
|
|
592
|
-
|
|
593
|
-
int rule_len;
|
|
594
|
-
|
|
595
|
-
//識別率
|
|
596
|
-
|
|
597
|
-
double ans_rate;
|
|
598
|
-
|
|
599
|
-
//ルール集合選択配列
|
|
600
|
-
|
|
601
|
-
int rule_select[N_rp];
|
|
602
|
-
|
|
603
|
-
//加重和適応度
|
|
604
|
-
|
|
605
|
-
double fitness;
|
|
606
|
-
|
|
607
|
-
|
|
608
|
-
|
|
609
|
-
//ルール集合選択後の結果
|
|
610
|
-
|
|
611
|
-
//ルール数
|
|
612
|
-
|
|
613
|
-
int rule_num_2;
|
|
614
|
-
|
|
615
|
-
//総ルール長
|
|
616
|
-
|
|
617
|
-
int rule_len_2;
|
|
618
|
-
|
|
619
|
-
//識別率
|
|
620
|
-
|
|
621
|
-
double ans_rate_2;
|
|
622
|
-
|
|
623
|
-
//ルール集合選択配列
|
|
624
|
-
|
|
625
|
-
int rule_select_2[N_rp];
|
|
626
|
-
|
|
627
|
-
|
|
628
|
-
|
|
629
|
-
|
|
630
|
-
|
|
631
|
-
|
|
632
|
-
|
|
633
|
-
};
|
|
634
|
-
|
|
635
|
-
|
|
636
|
-
|
|
637
|
-
|
|
638
|
-
|
|
639
|
-
int main() {
|
|
640
|
-
|
|
641
|
-
|
|
642
|
-
|
|
643
|
-
////////////////準備///////////////////////
|
|
644
|
-
|
|
645
|
-
//オブジェクト生成
|
|
646
|
-
|
|
647
|
-
Fuzzy fuzzy;
|
|
648
|
-
|
|
649
|
-
|
|
650
|
-
|
|
651
|
-
//学習データ読み込み
|
|
652
|
-
|
|
653
|
-
fuzzy.read_data();
|
|
654
|
-
|
|
655
|
-
|
|
656
|
-
|
|
657
|
-
/////////////////////学習開始/////////////////////////
|
|
658
|
-
|
|
659
|
-
////適合度計算
|
|
660
|
-
|
|
661
|
-
fuzzy.calc_fit();
|
|
662
|
-
|
|
663
|
-
////信頼度計算
|
|
664
|
-
|
|
665
|
-
fuzzy.calc_trust();
|
|
666
|
-
|
|
667
|
-
////結論部クラス決定、ルール重み計算
|
|
668
|
-
|
|
669
|
-
fuzzy.calc_class();
|
|
670
|
-
|
|
671
|
-
fuzzy.count_rule();
|
|
672
|
-
|
|
673
|
-
|
|
674
|
-
|
|
675
|
-
|
|
676
|
-
|
|
677
|
-
////////////未知パターン識別////////////////
|
|
678
|
-
|
|
679
|
-
////識別率計算
|
|
680
|
-
|
|
681
|
-
fuzzy.calc_ans();
|
|
682
|
-
|
|
683
|
-
|
|
684
|
-
|
|
685
|
-
fuzzy.show1();
|
|
686
|
-
|
|
687
|
-
|
|
688
|
-
|
|
689
|
-
|
|
690
|
-
|
|
691
|
-
////ファジィルール選択
|
|
692
|
-
|
|
693
|
-
fuzzy.create_rule(15);
|
|
694
|
-
|
|
695
|
-
|
|
696
|
-
|
|
697
|
-
fuzzy.show2();
|
|
698
|
-
|
|
699
|
-
|
|
700
|
-
|
|
701
|
-
return 0;
|
|
702
|
-
|
|
703
|
-
}
|
|
704
|
-
|
|
705
|
-
```
|
|
706
|
-
|
|
707
|
-
|
|
708
|
-
|
|
709
|
-
ファジィ識別器をC++で作成しています。show1,show2関数で識別率、ルール数、総ルール長を表示するようにしています。実行結果は、show1では、順に91.667,0,0となり、show2では93.0,0,0となりました。識別率に関しては正解データと一致しました。ただ、ルール数と総ルール長はshow1に関しては13,22で、show2に関しては5,8が正解となります。どこで間違っているのかがよく分からないのでよろしければ教えてください。
|
|
1
|
+
ファジィ識別器。ファジィ識別器ファジィ識別器ファジィ識別器ファジィ識別器
|