BPnetwork11/README.md

# BPnetwork11
#include <stdio.h>
#include <math.h>
#include <stdlib.h>
#include <time.h>

#define INNODE 2 // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>Ԫ<EFBFBD><D4AA><EFBFBD><EFBFBD>
#define HIDENODE 12// <20><><EFBFBD>ز<EFBFBD><D8B2><EFBFBD>Ԫ<EFBFBD><D4AA><EFBFBD><EFBFBD>
#define OUTNODE 1 // <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>Ԫ<EFBFBD><D4AA><EFBFBD><EFBFBD>

/**
 * <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ѧϰ<D1A7>ʣ<EFBFBD>
 */
double StudyRate = 1.2;

/**
 * <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
 */
double threshold = 1e-4;

/**
 * <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
 */
int mostTimes = 1e6;

/**
 * ѵ<><D1B5><EFBFBD><EFBFBD><EFBFBD><EFBFBD>С
 */
int trainSize = 0;

/**
 * <20><><EFBFBD>Լ<EFBFBD><D4BC><EFBFBD>С
 */
int testSize = 0;

/**
 * <20><><EFBFBD><EFBFBD>
 */
typedef struct Sample{
    double out[30][OUTNODE]; // <20><><EFBFBD>
    double in[30][INNODE]; // <20><><EFBFBD><EFBFBD>
}Sample;


/**
 * <20><>Ԫ<EFBFBD><D4AA><EFBFBD>
 */
typedef struct Node{
    double value; // <20><>ǰ<EFBFBD><C7B0>Ԫ<EFBFBD><D4AA><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ֵ
    double bias; // <20><>ǰ<EFBFBD><C7B0>Ԫ<EFBFBD><D4AA><EFBFBD>ƫƫ<C6AB><C6AB>ֵ
    double bias_delta; // <20><>ǰ<EFBFBD><C7B0>Ԫ<EFBFBD><D4AA><EFBFBD>ƫ<EFBFBD><C6AB>ֵ<EFBFBD><D6B5><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ֵ
    double *weight; // <20><>ǰ<EFBFBD><C7B0>Ԫ<EFBFBD><D4AA><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>һ<EFBFBD><D2BB><EFBFBD>㴫<EFBFBD><E3B4AB><EFBFBD><EFBFBD>Ȩֵ
    double *weight_delta; // <20><>ǰ<EFBFBD><C7B0>Ԫ<EFBFBD><D4AA><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>һ<EFBFBD><D2BB><EFBFBD>㴫<EFBFBD><E3B4AB><EFBFBD><EFBFBD>Ȩֵ<C8A8><D6B5><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ֵ
}Node;

/**
 *  <20><><EFBFBD><EFBFBD><EFBFBD>
 */
Node inputLayer[INNODE];
/**
 * <20><><EFBFBD>ز<EFBFBD>
 */
Node hideLayer[HIDENODE];
/**
 * <20><><EFBFBD><EFBFBD><EFBFBD>
 */
Node outLayer[OUTNODE];



double Max(double a, double b){
    return a > b ? a : b;
}

//<2F><><EFBFBD> 
double sigmoid(double x){
       double y,z;
       y=exp(x);
       z=y/(1+y);
       return z;
       
}


/**
 * <20><>ȡѵ<C8A1><D1B5><EFBFBD><EFBFBD>
 * @param filename <20>ļ<EFBFBD><C4BC><EFBFBD>
 * @return ѵ<><D1B5><EFBFBD><EFBFBD>
 */
Sample * getTrainData(const char * filename){
    Sample * result = (Sample*)malloc(sizeof (Sample));
    FILE * file = fopen(filename, "r");
    if(file != NULL){
        int count = 0;
        while (fscanf(file, "%lf %lf %lf", &result->in[count][0], &result->in[count][1], &result->out[count][0]) != EOF){
            ++count;
        }
        trainSize = count;
        printf("%s The file has been successfully read!\n", filename);
        fclose(file);
        return result;
    } else{
        fclose(file);
        printf("%s Encountered an error while opening the file!\n\a", filename);
        return NULL;
    }
}

/**
 * <20><>ȡ<EFBFBD><C8A1><EFBFBD>Լ<EFBFBD>
 * @param filename <20>ļ<EFBFBD><C4BC><EFBFBD>
 * @return <20><><EFBFBD>Լ<EFBFBD>
 */
Sample * getTestData(const char * filename){
    /*<2A><><EFBFBD>ڴ<EFBFBD><DAB4>з<EFBFBD><D0B7><EFBFBD><EFBFBD>㹻<EFBFBD>Ŀռ<C4BF><D5BC><EFBFBD><EFBFBD>洢һ<E6B4A2><D2BB>Sample<6C>ṹ<EFBFBD><E1B9B9><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ָ<EFBFBD><D6B8><EFBFBD><EFBFBD>ڴ<EFBFBD><DAB4><EFBFBD>ָ<EFBFBD><D6B8>洢<EFBFBD><E6B4A2>result<6C><74><EFBFBD><EFBFBD><EFBFBD><EFBFBD>*/
   Sample * result=(Sample*)malloc(sizeof(Sample)); 
   FILE * file = fopen(filename, "r");//<2F><><EFBFBD>ļ<EFBFBD>
   if(file!= NULL){
    // <20><>ʼ<EFBFBD><CABC>һ<EFBFBD><D2BB><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>count<6E><74><EFBFBD><EFBFBD><EFBFBD>ڸ<EFBFBD><DAB8>ٶ<EFBFBD>ȡ<EFBFBD><C8A1><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
     int count=0;
    /*<2A><><EFBFBD><EFBFBD>whileѭ<65><D1AD><EFBFBD>Ӳ<EFBFBD><D3B2>Լ<EFBFBD><D4BC>ļ<EFBFBD><C4BC><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ж<EFBFBD>ȡ<EFBFBD><C8A1><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ֱ<EFBFBD><D6B1><EFBFBD><EFBFBD>ȡ<EFBFBD><C8A1><EFBFBD>ļ<EFBFBD>ĩβ<C4A9><CEB2>
    ÿ<>γɹ<CEB3><C9B9><EFBFBD>ȡһ<C8A1><D2BB><EFBFBD><EFBFBD><EFBFBD>ݺ󣬵<DDBA><F3A3ACB5><EFBFBD>count<6E><74>*/
     while (fscanf(file, "%lf %lf", &result->in[count][0], &result->in[count][1])!=EOF){
            ++count;
        }
    //<2F><><EFBFBD><EFBFBD><EFBFBD>յ<EFBFBD>count<6E><74>ֵ<EFBFBD>洢<EFBFBD><E6B4A2><EFBFBD><EFBFBD>ΪtestSize<7A><65>ȫ<EFBFBD>ֱ<EFBFBD><D6B1><EFBFBD><EFBFBD>У<EFBFBD><D0A3>Ա<EFBFBD><D4B1><EFBFBD><EFBFBD>ʹ<EFBFBD><CAB9>
      testSize=count;
    printf("%s The file has been successfully read!\n", filename);
    fclose(file);
    //<2F><><EFBFBD><EFBFBD>result
    return result;
    
   }else{
        fclose(file);
        printf("%s Encountered an error while opening the file!\n\a", filename);
        return NULL;
    }
}

/**
 * <20><>ӡ<EFBFBD><D3A1><EFBFBD><EFBFBD>
 * @param data Ҫ<><D2AA>ӡ<EFBFBD><D3A1><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
 * @param size <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD>С
 */
void printData(Sample * data, int size){
	int i;
     if(data==NULL){
     	printf("Sample is empty!");
     	return;
	 }
	 else{
	 	for(i=0;i<testSize;i++)
		 {
	 			printf("%f %f ",data->in[i][0],data->in[i][1]);
			 printf("%f",data->out[i][0]);
			 printf("\n");
		 }
	 }
}

/**
 * <20><>ʼ<EFBFBD><CABC><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
 */
void init(){
    // <20><><EFBFBD><EFBFBD>ʱ<EFBFBD><CAB1><EFBFBD>Ϊ<EFBFBD><CEAA><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>е<EFBFBD><D0B5><EFBFBD><EFBFBD><EFBFBD>
   srand(time(NULL));
    
    // <20><><EFBFBD><EFBFBD><EFBFBD>ij<EFBFBD>ʼ<EFBFBD><CABC>
    for (int i = 0; i < INNODE; ++i) {
        inputLayer[i].weight = (double *)malloc(sizeof (double ) * HIDENODE);
        inputLayer[i].weight_delta = (double *) malloc(sizeof (double ) * HIDENODE);
        inputLayer[i].bias = 0.0;
        inputLayer[i].bias_delta = 0.0;
    }

    // <EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>Ȩֵ<EFBFBD><EFBFBD>ʼ<EFBFBD><EFBFBD>
    for (int i = 0; i < INNODE; ++i) {
        for (int j = 0; j < HIDENODE; ++j) {
            inputLayer[i].weight[j] = rand() % 10000 / (double )10000 * 2 - 1.0;
            inputLayer[i].weight_delta[j] = 0.0;
        }
    }


    // <EFBFBD><EFBFBD>ʼ<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ز<EFBFBD><EFBFBD><EFBFBD>
    for (int i = 0; i < HIDENODE; ++i) {
        /*Ϊ<><CEAA><EFBFBD>ز<EFBFBD>ڵ<EFBFBD> i <EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>һ<EFBFBD><EFBFBD> double <EFBFBD><EFBFBD><EFBFBD>͵<EFBFBD><EFBFBD><EFBFBD><EFBFBD>飬<EFBFBD><EFBFBD><EFBFBD>ڴ洢<EFBFBD>ýڵ<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>һ<EFBFBD><EFBFBD>ڵ㴫<EFBFBD><EFBFBD><EFBFBD><EFBFBD>Ȩ<EFBFBD>ء<EFBFBD>
        ʹ<EFBFBD><EFBFBD>malloc <EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ڶ<EFBFBD><EFBFBD>ڴ<EFBFBD><EFBFBD>з<EFBFBD><EFBFBD><EFBFBD><EFBFBD>㹻<EFBFBD>Ŀռ䣬<EFBFBD>Դ洢 OUTNODE <EFBFBD><EFBFBD> double <EFBFBD><EFBFBD><EFBFBD>͵<EFBFBD>Ȩ<EFBFBD><EFBFBD>ֵ<EFBFBD><EFBFBD>
        */
        
        hideLayer[i].weight = (double *)malloc(sizeof(double)*OUTNODE);
        /*Ϊ<><CEAA><EFBFBD>ز<EFBFBD>ڵ<EFBFBD> i <EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>һ<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ڴ洢Ȩ<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ֵ<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>顣<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>齫<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ѵ<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ڴ洢Ȩ<EFBFBD>صĸ<EFBFBD><EFBFBD><EFBFBD>ֵ<EFBFBD><EFBFBD>
        ʹ<EFBFBD><EFBFBD>malloc <EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ڶ<EFBFBD><EFBFBD>ڴ<EFBFBD><EFBFBD>з<EFBFBD><EFBFBD><EFBFBD><EFBFBD>㹻<EFBFBD>Ŀռ䣬<EFBFBD>Դ洢 OUTNODE <EFBFBD><EFBFBD> double <EFBFBD><EFBFBD><EFBFBD>͵<EFBFBD>Ȩ<EFBFBD><EFBFBD>ֵ<EFBFBD><EFBFBD>
        */
        hideLayer[i].weight_delta =(double*)malloc(sizeof(double)*OUTNODE);
        /*Ϊ<><CEAA><EFBFBD>ز<EFBFBD>ڵ<EFBFBD> i <EFBFBD><EFBFBD>ʼ<EFBFBD><EFBFBD><EFBFBD><EFBFBD>һ<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ƫ<EFBFBD><EFBFBD>ֵ<EFBFBD><EFBFBD>
        <EFBFBD><EFBFBD><EFBFBD>ֵͨ<EFBFBD><EFBFBD><EFBFBD><EFBFBD>һ<EFBFBD><EFBFBD><EFBFBD><EFBFBD> -1.0 <EFBFBD><EFBFBD> 1.0 ֮<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ڵ<EFBFBD><EFBFBD><EFBFBD><EFBFBD>ýڵ<EFBFBD>ļ<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ֵ<EFBFBD><EFBFBD>
        */
        hideLayer[i].bias =  rand() % 10000 / (double )10000 * 2 - 1.0;
        /*<2A><>ʼ<EFBFBD><CABC><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ز<EFBFBD>ڵ<EFBFBD> i <EFBFBD><EFBFBD>ƫ<EFBFBD><EFBFBD>ֵ<EFBFBD><EFBFBD><EFBFBD><EFBFBD>ֵ<EFBFBD><EFBFBD><EFBFBD><EFBFBD>ʼֵΪ0.0<EFBFBD><EFBFBD>*/
        hideLayer[i].bias_delta = 0.0;
    }
    
    // <EFBFBD><EFBFBD>ʼ<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ز<EFBFBD>Ȩֵ
    for (int i = 0; i < HIDENODE; ++i) {
        for (int j = 0; j < OUTNODE; ++j) {
            hideLayer[i].weight[j] = rand() % 10000 / (double )10000 * 2 - 1.0;
            hideLayer[i].weight_delta[j] = 0.0;
        }
    }

    for (int i = 0; i < OUTNODE; ++i) {
        outLayer[i].bias = rand() % 10000 / (double )10000 * 2 - 1.0;
        outLayer[i].bias_delta = 0.0;
    }
    
}

/**
 * <EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ֵ
 */
void resetDelta(){
    for (int i = 0; i < INNODE; ++i) {
        for (int j = 0; j < HIDENODE; ++j) {
            inputLayer[i].weight_delta[j] = 0.0;
        }
    }

    for (int i = 0; i < HIDENODE; ++i) {
        hideLayer[i].bias_delta = 0.0;
        for (int j = 0; j < OUTNODE; ++j) {
            hideLayer[i].weight_delta[j] = 0.0;
        }
    }

    for (int i = 0; i < OUTNODE; ++i) {
        outLayer[i].bias_delta = 0.0;
    }
}


int main() {
    // <EFBFBD><EFBFBD>ʼ<EFBFBD><EFBFBD>
    init();
    // <EFBFBD><EFBFBD>ȡѵ<EFBFBD><EFBFBD><EFBFBD><EFBFBD>
    Sample * trainSample = getTrainData("TrainData.txt");
//    printData(trainSample, trainSize);
          

    for (int trainTime = 0; trainTime < mostTimes; ++trainTime) {
        // <EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ݶ<EFBFBD><EFBFBD><EFBFBD>Ϣ
        resetDelta();

        // <EFBFBD><EFBFBD>ǰѵ<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
        double error_max = 0.0;

        // <EFBFBD><EFBFBD>ʼѵ<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ۼ<EFBFBD>bp<EFBFBD><EFBFBD>
        for (int currentTrainSample_Pos = 0; currentTrainSample_Pos < trainSize; ++currentTrainSample_Pos) {

            // <EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>Ա<EFBFBD><EFBFBD><EFBFBD>
            for (int inputLayer_Pos = 0; inputLayer_Pos < INNODE; ++inputLayer_Pos) {
                inputLayer[inputLayer_Pos].value = trainSample->in[currentTrainSample_Pos][inputLayer_Pos];
            }

            /** ----- <20><>ʼ<EFBFBD><CABC><EFBFBD>򴫲<EFBFBD> ----- */
            for (int hideLayer_Pos = 0; hideLayer_Pos < HIDENODE; ++hideLayer_Pos) {
                double sum = 0.0;
                for (int inputLayer_Pos = 0; inputLayer_Pos < INNODE; ++inputLayer_Pos) {
                    sum += inputLayer[inputLayer_Pos].value * inputLayer[inputLayer_Pos].weight[hideLayer_Pos];
                }

                sum -= hideLayer[hideLayer_Pos].bias;
                hideLayer[hideLayer_Pos].value = sigmoid(sum);
            }
            /**       <EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ز<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>㴫<EFBFBD><EFBFBD>  */ 
            for (int outLayer_Pos = 0;  outLayer_Pos < OUTNODE ; ++outLayer_Pos) {
                double sum = 0.0;
                for (int hideLayer_Pos = 0; hideLayer_Pos < HIDENODE; ++hideLayer_Pos) {
                    /*<2A><><EFBFBD><EFBFBD>ÿһ<C3BF><D2BB><EFBFBD><EFBFBD><EFBFBD>ز<EFBFBD>ڵ<EFBFBD><DAB5>value<EFBFBD><EFBFBD>Ȩֵ<EFBFBD>ij˻<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ӵõ<EFBFBD>sum*/
                    sum+=hideLayer[hideLayer_Pos].value * hideLayer[hideLayer_Pos].weight[outLayer_Pos];
                    
                }
                /*<2A><><EFBFBD><EFBFBD>sum<EFBFBD><EFBFBD>ʹsum<EFBFBD><EFBFBD>ȥƫ<EFBFBD><EFBFBD>ֵ;

                */sum-=outLayer[outLayer_Pos].bias;
                outLayer[outLayer_Pos].value=sigmoid(sum);
                /*<2A><><EFBFBD><EFBFBD>sigmod<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>Եõ<EFBFBD><EFBFBD><EFBFBD>sum<EFBFBD><EFBFBD><EFBFBD>м<EFBFBD><EFBFBD><EFBFBD>Ѽ<EFBFBD><EFBFBD><EFBFBD><EFBFBD>Ľ<EFBFBD><EFBFBD><EFBFBD><EFBFBD>ֵ<EFBFBD><EFBFBD><EFBFBD><EFBFBD>Ӧ<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ڵ<EFBFBD>value(outLayer[outLayer_Pos].value)<29><>
                
                */
            }


            /** ----- <EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD> ----- */
            double error = 0.0;
            for (int outLayer_Pos = 0; outLayer_Pos < OUTNODE; ++outLayer_Pos) {
                double temp = fabs(outLayer[outLayer_Pos].value - trainSample->out[currentTrainSample_Pos][outLayer_Pos]);
                // <20><>ʧ<EFBFBD><CAA7><EFBFBD><EFBFBD>
                error += temp * temp / 2.0;
            }
            
            error_max = Max(error_max, error);
            
            
            /** ----- <20><><EFBFBD>򴫲<EFBFBD> ----- */
            for (int outLayer_Pos = 0; outLayer_Pos < OUTNODE; ++outLayer_Pos) {
                double bias_delta = -(trainSample->out[currentTrainSample_Pos][outLayer_Pos] - outLayer[outLayer_Pos].value)
                        * outLayer[outLayer_Pos].value * (1.0 - outLayer[outLayer_Pos].value);
                outLayer[outLayer_Pos].bias_delta += bias_delta;
            }

            for (int hideLayer_Pos = 0; hideLayer_Pos < HIDENODE; ++hideLayer_Pos) {
                for (int outLayer_Pos = 0; outLayer_Pos < OUTNODE; ++outLayer_Pos) {
                    double weight_delta = (trainSample->out[currentTrainSample_Pos][outLayer_Pos] - outLayer[outLayer_Pos].value)
                                          * outLayer[outLayer_Pos].value * (1.0 - outLayer[outLayer_Pos].value)
                                          * hideLayer[hideLayer_Pos].value;
                    hideLayer[hideLayer_Pos].weight_delta[outLayer_Pos] += weight_delta;
                }
            }

            //
            for (int hideLayer_Pos = 0; hideLayer_Pos < HIDENODE; ++hideLayer_Pos) {
                double sum = 0.0;
                for (int outLayer_Pos = 0; outLayer_Pos < OUTNODE; ++outLayer_Pos) {
                    sum += -(trainSample->out[currentTrainSample_Pos][outLayer_Pos] - outLayer[outLayer_Pos].value)
                           * outLayer[outLayer_Pos].value * (1.0 - outLayer[outLayer_Pos].value)
                           * hideLayer[hideLayer_Pos].weight[outLayer_Pos];
                }
                hideLayer[hideLayer_Pos].bias_delta += sum * hideLayer[hideLayer_Pos].value * (1.0 - hideLayer[hideLayer_Pos].value);
            }


            for (int inputLayer_Pos = 0; inputLayer_Pos < INNODE; ++inputLayer_Pos) {
                for (int hideLayer_Pos = 0; hideLayer_Pos < HIDENODE; ++hideLayer_Pos) {
                    double sum  = 0.0;
                    for (int outLayer_Pos = 0; outLayer_Pos < OUTNODE; ++outLayer_Pos) {
                        sum += (trainSample->out[currentTrainSample_Pos][outLayer_Pos] - outLayer[outLayer_Pos].value)
                               * outLayer[outLayer_Pos].value * (1.0 - outLayer[outLayer_Pos].value)
                               * hideLayer[hideLayer_Pos].weight[outLayer_Pos];
                    }
                    inputLayer[inputLayer_Pos].weight_delta[hideLayer_Pos] += sum * hideLayer[hideLayer_Pos].value * (1.0 - hideLayer[hideLayer_Pos].value)
                                                                              * inputLayer[inputLayer_Pos].value;
                }
            }

        }


        // <20>ж<EFBFBD><D0B6><EFBFBD><EFBFBD><EFBFBD>Ƿ<EFBFBD>ﵽ<EFBFBD><EFB5BD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>Χ
        if(error_max < threshold){
            printf("\a Training completed!Total training count:%d,  maximum error is:%f\n", trainTime + 1, error_max);
            break;
        }

        // <EFBFBD><EFBFBD><EFBFBD><EFBFBD>޷<EFBFBD><EFBFBD><EFBFBD><EFBFBD>ܣ<EFBFBD><EFBFBD><EFBFBD>ʼ<EFBFBD><EFBFBD><EFBFBD><EFBFBD>

        for (int inputLayer_Pos = 0; inputLayer_Pos < INNODE; ++inputLayer_Pos) {
            for (int hideLayer_Pos = 0; hideLayer_Pos < HIDENODE; ++hideLayer_Pos) {
                inputLayer[inputLayer_Pos].weight[hideLayer_Pos] += StudyRate
                                                                    * inputLayer[inputLayer_Pos].weight_delta[hideLayer_Pos] /
                                                                    (double) trainSize;
            }
        }

        for (int hideLayer_Pos = 0; hideLayer_Pos < HIDENODE; ++hideLayer_Pos) {
            hideLayer[hideLayer_Pos].bias += StudyRate
                    * hideLayer[hideLayer_Pos].bias_delta / (double )trainSize;
            for (int outLayer_Pos = 0; outLayer_Pos < OUTNODE; ++outLayer_Pos) {
                hideLayer[hideLayer_Pos].weight[outLayer_Pos] += StudyRate
                        * hideLayer[hideLayer_Pos].weight_delta[outLayer_Pos] / (double )trainSize;
            }
        }

        for (int outLayer_Pos = 0; outLayer_Pos < OUTNODE; ++outLayer_Pos) {
            outLayer[outLayer_Pos].bias += StudyRate
                    * outLayer[outLayer_Pos].bias_delta / (double )trainSize;
        }
    }

    // ѵ<EFBFBD><EFBFBD><EFBFBD><EFBFBD>ɣ<EFBFBD><EFBFBD><EFBFBD>ȡ<EFBFBD><EFBFBD><EFBFBD>Լ<EFBFBD>
    Sample * testSample = getTestData("TestData.txt");
    printf("The predicted results are as follows:\n");
    for (int currentTestSample_Pos = 0; currentTestSample_Pos < testSize; ++currentTestSample_Pos) {
        for (int inputLayer_Pos = 0; inputLayer_Pos < INNODE; ++inputLayer_Pos) {
            inputLayer[inputLayer_Pos].value = testSample->in[currentTestSample_Pos][inputLayer_Pos];
        }

        for (int hideLayer_Pos = 0; hideLayer_Pos < HIDENODE; ++hideLayer_Pos) {
            double sum = 0.0;
            for (int inputLayer_Pos = 0; inputLayer_Pos < INNODE; ++inputLayer_Pos) {
                sum += inputLayer[inputLayer_Pos].value * inputLayer[inputLayer_Pos].weight[hideLayer_Pos];
        }
            sum -= hideLayer[hideLayer_Pos].bias;
            hideLayer[hideLayer_Pos].value = sigmoid(sum);
        }

        for (int outLayer_Pos = 0; outLayer_Pos < OUTNODE; ++outLayer_Pos) {
            double sum = 0.0;
            for (int hideLayer_Pos = 0; hideLayer_Pos < HIDENODE; ++hideLayer_Pos) {
                sum += hideLayer[hideLayer_Pos].value * hideLayer[hideLayer_Pos].weight[outLayer_Pos];
            }
            sum -= outLayer[outLayer_Pos].bias;
            outLayer[outLayer_Pos].value = sigmoid(sum);
        }

        for (int outLayer_Pos = 0; outLayer_Pos < OUTNODE; ++outLayer_Pos) {
            testSample->out[currentTestSample_Pos][outLayer_Pos] = outLayer[outLayer_Pos].value;
        }
    }
    printData(testSample, testSize);
    return 0;
}