q1.java

销售预测的实现,包括移动平均,指数平滑,时间序列分解,自回归

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package forcast;

/**
 *
 * @author Administrator
 */
/*public class q1 {

	public static void main(String[] args) {

		double x[][]=new double[2][];
		x[0]=new double[]{-0.5,-0.5,0.3,0.1,-0.1,0.8,0.2,0.3};
		x[1]=new double[]{0.3,-0.2,-0.6,0.1,-0.5,1.0,0.3,0.9};

		int t[]={1,0,0,1,0,1,1,1};
		double y[]=new double[2];
		double tt[]=new double[1];
		Util_xxz.init();
		double temp1[]=new double[8];
		double temp2[]=new double[8];
	    for(int k=0;k<10000000;k++)
	    {

	    	for(int i=0;i<8;i++)
	    	{
			y[0]= x[0][i];y[1]= x[1][i];
			tt[0]=t[i];
			Util_xxz.bp(y,tt);
			}
	    	double s=0;
	    	for(int l=0;l<8;l++)
	    	{
			y[0]= x[0][l];y[1]= x[1][l];
			double temp=Util_xxz.result(y);
			s=s+(temp-t[l])*(temp-t[l]);
			temp1[l]=temp;
			temp2[l]=temp;
		    }
	    	s=s/2;
	    	if(s<0.001){
	    		 for(int m=0;m<8;m++)

	    		System.out.println("("+temp1[m]+":"+temp2[m]+")");
	    		break;}




	    }
	  System.out.print("______________");
	   for(int l=0;l<8;l++)
    	{
		y[0]= x[0][l];y[1]= x[1][l];
		System.out.println(Util_xxz.result(y));

	    }
	   System.out.println("_____________");
	   Util_xxz.showW();

	}


}*/