ken1983414 发表于 2006-11-22 22:46

神经网络BP算法

神经网络BP算法(vC++程序)
                                       

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; /*/单个样本输入数据*/
double T; /*/单个样本教师数据*/
double W; /*/输入层至隐层权值*/
double V; /*/隐层至输出层权值*/
double X; /*/隐层的输入*/
double Y; /*/输出层的输入*/
double H; /*/隐层的输出*/
double O; /*/输出层的输出*/
double YU_HN; /*/隐层的阈值*/
double YU_ON; /*/输出层的阈值*/
double err_m; /*/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;

FILE *fp;
/*定义一个放学习样本的结构*/
struct {
double input;
double teach;
}Study_Data;

/*改进型bp算法用来保存每次计算的权值*/
struct {
double old_W;
double old_V;
}Old_WV;


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.input=datr;
      /*printf("\nthe Study_Datat[%d].input[%d]=%f\n",m,i,Study_Data.input);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.teach=datr;
       /*printf("\nThe Study_Data[%d].teach[%d]=%f",m,i,Study_Data.teach);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.input);
   }
for(j=0;j   {printf("\nStudy_Data[%d].teach[%d]=%f",m,j,Study_Data.teach);
   }
}
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=(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);
   }
}
for(ii=0;ii {
for(jj=0;jj   {V= (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);
   }
}
for(k=0;k {
YU_HN = (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);
}
for(kk=0;kk {
YU_ON = (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=Study_Data.input;
   printf("P[%d]=%f\n",i,P);
}
/*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;kT=Study_Data.teach;
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*P;/*求隐层内积*/
    }

   X=sigma-YU_HN;/*求隐层净输入,为什么减隐层的阀值*/
   H=1.0/(1.0+exp(-X));/*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*H;
}
Y=sigma-YU_ON;
O=1.0/(1.0+exp(-Y));
}
return 1;
}


int Err_O_H(int m)
{int k;
double abs_err;
double sqr_err=0;
for (k=0;k{
abs_err=T-O;
sqr_err+=(abs_err)*(abs_err);
d_err=abs_err*O*(1.0-O);
err_m=sqr_err/2;
}
return 1;
}


double e_err;
int Err_H_I()
{
int j,k;
double sigma;
for(j=0;j {
sigma=0.0;
for(k=0;k{
   sigma=d_err*V;
   }
e_err=sigma*H*(1-H);
}
return 1;
}


saveWV(int m)
{int i;
int ii;
int j;
int jj;
for(i=0;i{
   for(j=0;j    {
   Old_WV.old_W = W;
    }
}
for(ii=0;ii{
   for(jj=0;jj    {
   Old_WV.old_V = V;
    }
}
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=V+a*d_err*H;
      }
   YU_ON+=a*d_err;
    }
}
else if(n>1)
{
   for (k=0;k    {
   for (j=0;j      {
       V=V+a*d_err*H+alpha*(V-Old_WV[(n-1)].old_V);
      }
   YU_ON+=a*d_err;
    }
}
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=W+b*e_err*P;
   }
    YU_HN+=b*e_err;
   }
}
else if(n>1)
{
for(j=0;j   {
    for(i=0;i   {
      W=W+b*e_err*P+alpha*(W-Old_WV[(n-1)].old_W);
   }
    YU_HN+=b*e_err;
   }
}
return 1;
}


double Err_Sum()
{int m;
double total_err=0;
for(m=0;m {
total_err+=err_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;jfprintf(fp,"W[%d][%d]=%f\n",i,j,W);
}
fprintf(fp,"\n");
for(ii=0;ii {
for(jj=0;jjfprintf(fp,"V[%d][%d]=%f\n",ii,jj,V);
}
fclose(fp);
printf("\nThe result of “权值.txt”(quanzhi) has been saved successfully!\nPress any key to continue...");
getch();


if((fp=fopen("f:\\bp\\阈值.txt","a"))==NULL)         /*save the result at f:\hsz\bpc\*/
{
printf("Cannot open file strike any key exit!");
getch();
exit(1);
}
fprintf(fp,"Save the result of “输出层的阈值”(huozhi) as follows:\n");
for(k=0;k   fprintf(fp,"YU_ON[%d]=%f\n",k,YU_ON);

fprintf(fp,"\nSave the result of “隐层的阈值为”(huozhi) as follows:\n");
for(kk=0;kkfprintf(fp,"YU_HN[%d]=%f\n",kk,YU_HN);

fclose(fp);
printf("\nThe result of “阈值.txt”(huozhi) has been saved successfully!\nPress any key to continue...");
getch();
}

/**********************/
/**程序入口,即主程序**/
/**********************/

void main()
{double Pre_error;
double sum_err;
int study;
int flag;
flag=30000;
a=0.7;
b=0.7;
alpha=0.9;
study=0;
Pre_error=0.0001;/*实际值为Pre_error=0.0001;*/

Start_Show();
GetTrainingData();
initial();

do
{int m;
++study;
for(m=0;m   {
    input_P(m);
    input_T(m);
    H_I_O();
    O_I_O();
    Err_O_H(m);
    Err_H_I();
    saveWV(m);         /****************/
    Delta_O_H(m);                           /*(m,study)*/
    Delta_H_I(m);                              /*(m,study)*/
   }
sum_err=Err_Sum();
printf("sum_err=%f\n",sum_err);
printf("Pre_error=%f\n\n",Pre_error);

if(study>flag)
   {
    printf("\n*******************************\n");
    printf("The program is ended by itself because of error!\nThe learning times is surpassed!\n");
    printf("*****************************\n");
    getch();
    break;
   }

}while (sum_err>Pre_error);

printf("\n****************\n");
printf("\nThe program have studyed for [%d] times!\n",study);
printf("\n****************\n");
savequan();      /*save the results*/
End_Show();
}
==========================

权值.txt

{Save the result of “权值”(quanzhi) as follows:
W=0.350578
W=-1.008697
W=-0.962250
W=0.055661
W=-0.372367
W=-0.890795
W=0.129752
W=-0.332591
W=-0.521561

V=-2.932654
V=-3.720583
V=-2.648183
V=2.938970
V=1.633281
V=1.944077

}

阈值.txt

{Save the result of “输出层的阈值”(huozhi) as follows:
YU_ON=-4.226843
YU_ON=1.501791

Save the result of “隐层的阈值为”(huozhi) as follows:
YU_HN=-0.431459
YU_HN=0.452127
YU_HN=0.258449

}

==================================

以上程序为VC++的程序改制而成!

[ 本帖最后由 风花雪月 于 2006-11-29 07:53 编辑 ]

xmwhit 发表于 2006-11-23 09:33

算法很简单,编写和调试程序却不太容易,楼主辛苦了。

ascendman 发表于 2006-12-28 14:55

赞一个

向你学习
页: [1]
查看完整版本: 神经网络BP算法