BP.rar_BP_BP 神经网络_BP神经网络 c_C语言_神经网络c语言

文件输入输出目录为：F:\BP\ 训练样本文件名：训练样本.txt 值为： 1 1 -1 1 -1 1 0 1 0 1 输出文件名为：阈值.txt 权值.txt ＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝ #include "stdlib.h" #include "math.h" #include "conio.h" #include "stdio.h" #define N 2 /*/学习样本个数*/ #define IN 3 /*/输入层神经元数目*/ #define HN 3 /*/隐层神经元数目*/ #define ON 2 /*/输出层神经元数目*/ #define Z 20 /*/旧权值保存-》每次study的权值都保存下来*/ double P[IN]; /*/单个样本输入数据*/ double T[ON]; /*/单个样本教师数据*/ double W[HN][IN]; /*/输入层至隐层权值*/ double V[ON][HN]; /*/隐层至输出层权值*/ double X[HN]; /*/隐层的输入*/ double Y[ON]; /*/输出层的输入*/ double H[HN]; /*/隐层的输出*/ double O[ON]; /*/输出层的输出*/ double YU_HN[HN]; /*/隐层的阈值*/ double YU_ON[ON]; /*/输出层的阈值*/ double err_m[N]; /*/第m个样本的总误差*/ double a; /*/输出层至隐层的学习效率*/ double b; /*/隐层至输入层学习效率*/ double alpha; /*/动量因子，改进型bp算法使用*/ double d_err[ON]; FILE *fp; /*定义一个放学习样本的结构*/ struct { double input[IN]; double teach[ON]; }Study_Data[N]; /*改进型bp算法用来保存每次计算的权值*/ struct { double old_W[HN][IN]; double old_V[ON][HN]; }Old_WV[Z]; int Start_Show() { clrscr(); printf("\n ***********************\n"); printf(" * Welcome to use *\n"); printf(" * this program of *\n"); printf(" * calculating the BP *\n"); printf(" * model! *\n"); printf(" * Happy every day! *\n"); printf(" ***********************\n"); printf("\n\nBefore starting,please read the follows carefully:\n\n"); printf(" 1.Please ensure the Path of the '训练样本.txt'(xunlianyangben.txt) is \ncorrect,like 'F:\BP\训练样本.txt'!\n"); printf(" 2.The calculating results will be saved in the Path of 'F:\\BP\\'!\n"); printf(" 3.The program will load 10 datas when running from 'F:\\BP\\训练样本.txt'!\n"); printf(" 4.The program of BP can study itself for no more than 30000 times.\nAnd surpassing the number,the program will be ended by itself in\npreventing running infinitely because of error!\n"); printf("\n\n\n"); printf("Now press any key to start...\n"); getch(); getch(); clrscr(); } int End_Show() { printf("\n\n---------------------------------------------------\n"); printf("The program has reached the end successfully!\n\nPress any key to exit!\n\n"); printf("\n ***********************\n"); printf(" * This is the end *\n"); printf(" * of the program which*\n"); printf(" * can calculate the BP*\n"); printf(" * model! *\n"); printf(" ***********************\n"); printf(" * Thanks for using! *\n"); printf(" * Happy every day! *\n"); printf(" ***********************\n"); getch(); exit(0); } GetTrainingData() /*OK*/ { int m,i,j; int datr; if((fp=fopen("f:\\bp\\训练样本.txt","r"))==NULL) /*读取训练样本*/ { printf("Cannot open file strike any key exit!"); getch(); exit(1); } m=0; i=0; j=0; while(fscanf(fp,"%d",&datr)!=EOF) {j++; if(j<=(N*IN)) {if(i { Study_Data[m].input[i]=datr; /*printf("\nthe Study_Datat[%d].input[%d]=%f\n",m,i,Study_Data[m].input[i]);getch();*/ /*use to check the loaded training datas*/ } if(m==(N-1)&&i==(IN-1)) { m=0; i=-1; } if(i==(IN-1)) { m++; i=-1; } } else if((N*IN) {if(i {Study_Data[m].teach[i]=datr; /*printf("\nThe Study_Data[%d].teach[%d]=%f",m,i,Study_Data[m].teach[i]);getch();*/ /*use to check the loaded training datas*/ } if(m==(N-1)&&i==(ON-1)) printf("\n"); if(i==(ON-1)) {m++; i=-1; } } i++; } fclose(fp); printf("\nThere are [%d] datats that have been loaded successfully!\n",j); /*show the data which has been loaded!*/ printf("\nShow the data which has been loaded as follows:\n"); for(m=0;m {for(i=0;i {printf("\nStudy_Data[%d].input[%d]=%f",m,i,Study_Data[m].input[i]); } for(j=0;j {printf("\nStudy_Data[%d].teach[%d]=%f",m,j,Study_Data[m].teach[j]); } } printf("\n\nPress any key to start calculating..."); getch(); return 1; } /*///////////////////////////////////*/ /*初始化权、阈值子程序*/ /*///////////////////////////////////*/ initial() {int i; int ii; int j; int jj; int k; int kk; /*隐层权、阈值初始化*/ for(i=0;i { for(j=1;j {W[i][j]=(double)((rand()/32767.0)*2-1); /*初始化输入层到隐层的权值，随机模拟0 和 1 -1 */ printf("w[%d][%d]=%f\n",i,j,W[i][j]); } } for(ii=0;ii { for(jj=0;jj {V[ii][jj]= (double)((rand()/32767.0)*2-1); /*初始化隐层到输出层的权值，随机模拟0 和 1 -1*/ printf("V[%d][%d]=%f\n",ii,jj,V[ii][jj]); } } for(k=0;k { YU_HN[k] = (double)((rand()/32767.0)*2-1); /*隐层阈值初始化 ,-0.01 ~ 0.01 之间*/ printf("YU_HN[%d]=%f\n",k,YU_HN[k]); } for(kk=0;kk { YU_ON[kk] = (double)((rand()/32767.0)*2-1); /*输出层阈值初始化 ,-0.01 ~ 0.01 之间*/ } return 1; }/*子程序initial()结束*/ /*//////////////////////////////////////////*/ /*第m个学习样本输入子程序*/ /*/////////////////////////////////////////*/ input_P(int m) { int i,j; for(i=0;i {P[i]=Study_Data[m].input[i]; printf("P[%d]=%f\n",i,P[i]); } /*获得第m个样本的数据*/ return 1; }/*子程序input_P(m）结束*/ /*/////////////////////////////////////////*/ /*第m个样本教师信号子程序*/ /*/////////////////////////////////////////*/ input_T(int m) {int k; for(k=0;k T[k]=Study_Data[m].teach[k]; return 1; }/*子程序input_T(m)结束*/ H_I_O() { double sigma; int i,j; for(j=0;j { sigma=0; for(i=0;i {sigma+=W[j][i]*P[i];/*求隐层内积*/ } X[j]=sigma-YU_HN[i];/*求隐层净输入，为什么减隐层的阀值*/ H[j]=1.0/(1.0+exp(-X[j]));/*求隐层输出 siglon算法*/ } return 1; }/*子程序H_I_O()结束*/ O_I_O() {int k; int j; double sigma; for(k=0;k { sigma=0.0; for(j=0;j { sigma+=V[k][j]*H[k]; } Y[k]=sigma-YU_ON[k]; O[k]=1.0/(1.0+exp(-Y[k])); } return 1; } int Err_O_H(int m) {int k; double abs_err[ON]; double sqr_err=0; for (k=0;k { abs_err[k]=T[k]-O[k]; sqr_err+=(abs_err[k])*(abs_err[k]); d_err[k]=abs_err[k]*O[k]*(1.0-O[k]); err_m[m]=sqr_err/2; } return 1; } double e_err[HN]; int Err_H_I() { int j,k; double sigma; for(j=0;j { sigma=0.0; for(k=0;k { sigma=d_err[k]*V[k][j]; } e_err[j]=sigma*H[j]*(1-H[j]); } return 1; } saveWV(int m) {int i; int ii; int j; int jj; for(i=0;i { for(j=0;j { Old_WV[m].old_W[i][j] = W[i][j]; } } for(ii=0;ii { for(jj=0;jj { Old_WV[m].old_V[ii][jj] = V[ii][jj]; } } return 1; } int Delta_O_H(int n) /*(int m,int n)*/ {int k,j; if(n<1) /*n<=1*/ { for (k=0;k { for (j=0;j { V[k][j]=V[k][j]+a*d_err[k]*H[j]; } YU_ON[k]+=a*d_err[k]; } } else if(n>1) { for (k=0;k { for (j=0;j { V[k][j]=V[k][j]+a*d_err[k]*H[j]+alpha*(V[k][j]-Old_WV[(n-1)].old_V[k][j]); } YU_ON[k]+=a*d_err[k]; } } return 1; } Delta_H_I(int n) /*(int m,int n)*/ { int i,j; if(n<=1) /*n<=1*/ { for (j=0;j { for (i=0;i { W[j][i]=W[j][i]+b*e_err[j]*P[i]; } YU_HN[j]+=b*e_err[j]; } } else if(n>1) { for(j=0;j { for(i=0;i { W[j][i]=W[j][i]+b*e_err[j]*P[i]+alpha*(W[j][i]-Old_WV[(n-1)].old_W[j][i]); } YU_HN[j]+=b*e_err[j]; } } return 1; } double Err_Sum() {int m; double total_err=0; for(m=0;m { total_err+=err_m[m]; } return total_err; } void savequan() { int i,j,k; int ii,jj,kk; if((fp=fopen("f:\\bp\\权值.txt","a"))==NULL) /*save the result at f:\hsz\bpc\*.txt*/ { printf("Cannot open file strike any key exit!"); getch(); exit(1); } fprintf(fp,"Save the result of “权值”(quanzhi) as follows:\n"); for(i=0;i { for(j=0;j fprintf(fp,"W[%d][%d]=%f\n",i,j,W[i][j]); } fprintf(fp,"\n"); for(ii=0;