using System;using System.IO;using System.Text;namespace BpANNet{ /// <summary> /// BpNet 的摘要说明。 /// </summary> public class BpNet { public int inNum;//输入节点数 int hideNum;//隐层节点数 public int outNum;//输出层节点数 public int sampleNum;//样本总数 Random R; double [] x;//输入节点的输入数据 double [] x1;//隐层节点的输出 double [] x2;//输出节点的输出
double [] o1;//隐层的输入 double [] o2;//输出层的输入 public double [,] w;//权值矩阵w public double [,] v;//权值矩阵V public double [,] dw;//权值矩阵w public double [,] dv;//权值矩阵V
public double rate;//学习率 public double [] b1;//隐层阈值矩阵 public double [] b2;//输出层阈值矩阵 public double [] db1;//隐层阈值矩阵 public double [] db2;//输出层阈值矩阵 double [] pp;//输出层的误差 double [] qq;//隐层的误差 double [] yd;//输出层的教师数据 public double e;//均方误差 double in_rate;//归一化比例系数
public int computeHideNum(int m,int n) { double s=Math.Sqrt(0.43*m*n+0.12*n*n+2.54*m+0.77*n+0.35)+0.51; int ss=Convert.ToInt32(s); return ((s-(double)ss)>0.5) ? ss+1:ss;
} public BpNet(double [,] p,double [,] t) { // 构造函数逻辑 R=new Random(); this.inNum=p.GetLength(1); this.outNum=t.GetLength(1); this.hideNum=computeHideNum(inNum,outNum);// this.hideNum=18; this.sampleNum=p.GetLength(0);
Console.WriteLine("输入节点数目： "+inNum); Console.WriteLine("隐层节点数目："+hideNum); Console.WriteLine("输出层节点数目："+outNum); Console.ReadLine();
x=new double[inNum]; x1=new double[hideNum]; x2=new double[outNum];
o1=new double[hideNum]; o2=new double[outNum];
w=new double[inNum,hideNum]; v=new double[hideNum,outNum]; dw=new double[inNum,hideNum]; dv=new double[hideNum,outNum]; b1=new double[hideNum]; b2=new double[outNum]; db1=new double[hideNum]; db2=new double[outNum]; pp=new double[hideNum]; qq=new double[outNum]; yd=new double[outNum];
//初始化w for(int i=0;i<inNum;i++) { for(int j=0;j<hideNum;j++) { w[i,j]=(R.NextDouble()*2-1.0)/2; } }
//初始化v for(int i=0;i<hideNum;i++) { for(int j=0;j<outNum;j++) { v[i,j]=(R.NextDouble()*2-1.0)/2; } }
rate=0.8; e=0.0; in_rate=1.0; }
//训练函数 public void train(double [,] p,double [,] t) { e=0.0; //求p，t中的最大值 double pMax=0.0; for(int isamp=0;isamp<sampleNum;isamp++) { for(int i=0;i<inNum;i++) { if(Math.Abs(p[isamp,i])>pMax) { pMax=Math.Abs(p[isamp,i]); } }
for(int j=0;j<outNum;j++) { if(Math.Abs(t[isamp,j])>pMax) { pMax=Math.Abs(t[isamp,j]); } }
in_rate=pMax; }//end isamp
for(int isamp=0;isamp<sampleNum;isamp++) { //数据归一化 for(int i=0;i<inNum;i++) { x[i]=p[isamp,i]/in_rate; } for(int i=0;i<outNum;i++) { yd[i]=t[isamp,i]/in_rate; }
//计算隐层的输入和输出
for(int j=0;j<hideNum;j++) { o1[j]=0.0; for(int i=0;i<inNum;i++) { o1[j]+=w[i,j]*x[i]; } x1[j]=1.0/(1.0+Math.Exp(-o1[j]-b1[j])); }
//计算输出层的输入和输出 for(int k=0;k<outNum;k++) { o2[k]=0.0; for(int j=0;j<hideNum;j++) { o2[k]+=v[j,k]*x1[j]; } x2[k]=1.0/(1.0+Math.Exp(-o2[k]-b2[k])); }
//计算输出层误差和均方差
for(int k=0;k<outNum;k++) { qq[k]=(yd[k]-x2[k])*x2[k]*(1.0-x2[k]); e+=(yd[k]-x2[k])*(yd[k]-x2[k]); //更新V for(int j=0;j<hideNum;j++) { v[j,k]+=rate*qq[k]*x1[j]; } }
//计算隐层误差
for(int j=0;j<hideNum;j++) { pp[j]=0.0; for(int k=0;k<outNum;k++) { pp[j]+=qq[k]*v[j,k]; } pp[j]=pp[j]*x1[j]*(1-x1[j]);
//更新W
for(int i=0;i<inNum;i++) { w[i,j]+=rate*pp[j]*x[i]; } }
//更新b2 for(int k=0;k<outNum;k++) { b2[k]+=rate*qq[k]; } //更新b1 for(int j=0;j<hideNum;j++) { b1[j]+=rate*pp[j]; }
}//end isamp e=Math.Sqrt(e);// adjustWV(w,dw);// adjustWV(v,dv); }//end train
public void adjustWV(double [,] w,double[,] dw) { for(int i=0;i<w.GetLength(0);i++) { for(int j=0;j<w.GetLength(1);j++) { w[i,j]+=dw[i,j]; } }
}
public void adjustWV(double [] w,double[] dw) { for(int i=0;i<w.Length;i++) { w[i]+=dw[i]; }
}
//数据仿真函数 public double[] sim(double [] psim) { for(int i=0;i<inNum;i++) x[i]=psim[i]/in_rate;
for(int j=0;j<hideNum;j++) { o1[j]=0.0; for(int i=0;i<inNum;i++) o1[j]=o1[j]+w[i,j]*x[i]; x1[j]=1.0/(1.0+Math.Exp(-o1[j]-b1[j])); } for(int k=0;k<outNum;k++) { o2[k]=0.0; for(int j=0;j<hideNum;j++) o2[k]=o2[k]+v[j,k]*x1[j]; x2[k]=1.0/(1.0+Math.Exp(-o2[k]-b2[k])); x2[k]=in_rate*x2[k];
}
return x2; } //end sim
//保存矩阵w,v public void saveMatrix(double [,] w,string filename) { StreamWriter sw=File.CreateText(filename); for(int i=0;i<w.GetLength(0);i++) { for(int j=0;j<w.GetLength(1);j++) { sw.Write(w[i,j]+" "); } sw.WriteLine(); } sw.Close();
}
//保存矩阵b1,b2 public void saveMatrix(double [] b,string filename) { StreamWriter sw=File.CreateText(filename); for(int i=0;i<b.Length;i++) { sw.Write(b[i]+" "); } sw.Close(); }
//读取矩阵W,V public void readMatrixW(double [,] w,string filename) { StreamReader sr; try { sr = new StreamReader(filename,Encoding.GetEncoding("gb2312")); String line; int i=0; while ((line = sr.ReadLine()) != null) {
string[] s1=line.Trim().Split(' '); for(int j=0;j<s1.Length;j++) { w[i,j]=Convert.ToDouble(s1[j]); } i++; } sr.Close(); } catch (Exception e) { // Let the user know what went wrong. Console.WriteLine("The file could not be read:"); Console.WriteLine(e.Message); } }
//读取矩阵b1,b2 public void readMatrixB(double [] b,string filename) { StreamReader sr; try { sr = new StreamReader(filename,Encoding.GetEncoding("gb2312")); String line; int i=0; while ((line = sr.ReadLine()) != null) { b[i]=Convert.ToDouble(line); i++; } sr.Close(); } catch (Exception e) { // Let the user know what went wrong. Console.WriteLine("The file could not be read:"); Console.WriteLine(e.Message); }
}
}//end bpnet} //end namespace
namespace BpANNet{ /// <summary> /// Class1 的摘要说明。 /// </summary> class Class1 { /// <summary> /// 应用程序的主入口点。 /// </summary> [STAThread] static void Main(string[] args) { //0.1399,0.1467,0.1567,0.1595,0.1588,0.1622,0.1611,0.1615,0.1685,0.1789,0.1790 // double [,] p1=new double[,]{{0.05,0.02},{0.09,0.11},{0.12,0.20},{0.15,0.22},{0.20,0.25},{0.75,0.75},{0.80,0.83},{0.82,0.80},{0.90,0.89},{0.95,0.89},{0.09,0.04},{0.1,0.1},{0.14,0.21},{0.18,0.24},{0.22,0.28},{0.77,0.78},{0.79,0.81},{0.84,0.82},{0.94,0.93},{0.98,0.99}};// double [,] t1=new double[,]{{1,0},{1,0},{1,0},{1,0},{1,0},{0,1},{0,1},{0,1},{0,1},{0,1},{1,0},{1,0},{1,0},{1,0},{1,0},{0,1},{0,1},{0,1},{0,1},{0,1}}; double [,] p1=new double[,]{{0.1399,0.1467,0.1567,0.1595,0.1588,0.1622},{0.1467,0.1567,0.1595,0.1588,0.1622,0.1611},{0.1567,0.1595,0.1588,0.1622,0.1611,0.1615},{0.1595,0.1588,0.1622,0.1611,0.1615,0.1685},{0.1588,0.1622,0.1611,0.1615,0.1685,0.1789}}; double [,] t1=new double[,]{{0.1622},{0.1611},{0.1615},{0.1685},{0.1789},{0.1790}}; BpNet bp=new BpNet(p1,t1); int study=0; do { study++; bp.train(p1,t1);// bp.rate=0.95-(0.95-0.3)*study/50000;// Console.Write("第 "+ study+"次学习： ");// Console.WriteLine(" 均方差为 "+bp.e); }while(bp.e>0.001 && study <50000); Console.Write("第 "+ study+"次学习： "); Console.WriteLine(" 均方差为 "+bp.e); bp.saveMatrix(bp.w,"w.txt"); bp.saveMatrix(bp.v,"v.txt"); bp.saveMatrix(bp.b1,"b1.txt"); bp.saveMatrix(bp.b2,"b2.txt");
// double [,] p2=new double[,]{{0.05,0.02},{0.09,0.11},{0.12,0.20},{0.15,0.22},{0.20,0.25},{0.75,0.75},{0.80,0.83},{0.82,0.80},{0.90,0.89},{0.95,0.89},{0.09,0.04},{0.1,0.1},{0.14,0.21},{0.18,0.24},{0.22,0.28},{0.77,0.78},{0.79,0.81},{0.84,0.82},{0.94,0.93},{0.98,0.99}}; double [,] p2=new double[,]{{0.1399,0.1467,0.1567,0.1595,0.1588,0.1622},{0.1622,0.1611,0.1615,0.1685,0.1789,0.1790}}; int aa=bp.inNum; int bb=bp.outNum; int cc=p2.GetLength(0); double [] p21=new double[aa]; double [] t2=new double[bb]; for(int n=0;n<cc;n++) { for(int i=0;i<aa;i++) { p21[i]=p2[n,i]; } t2=bp.sim(p21);
for(int i=0;i<t2.Length;i++) { Console.WriteLine(t2[i]+" "); }
}
Console.ReadLine(); } }}
