pcann.m

粒子群算法

function [ output_args ] = Untitled2( input_args )
%UNTITLED2 Summary of this function goes here
%  Detailed explanation goes here
clear;
H1=xlsread('testy.xls',1,'A1:J60');
len=size(H1,1);
H2=H1(:,9);
delta=(max(H2)-min(H2));  %反归一
delta1=min(H2); 
%   [b,a]= butter(5,0.5);
%   H1=filtfilt(b,a,H);

data=H1;
data=(data-ones(size(data,1),1)*min(data))./(ones(size(data,1),1)*(max(data)-min(data)));
H1=data ;


% A1=H1(1:40,1:8);
% B1=H1(1:40,9);
% C1=H1(41:60,1:8);
% D1=H1(41:60,9);
 k=1;
 for L=1:len
     
     switch L
         case 1
             A1=H1(2:len,1:8);
             B1=H1(2:len,9);
             C1=H1(1,1:8);
             D1=H1(1,9);
         case len
             A1=H1(1:len-1,1:8);
             B1=H1(1:len-1,9);
             C1=H1(len,1:8);
             D1=H1(len,9);

         otherwise
             A1=[H1(1:L-1,1:8);H1(L+1:len,1:8)];
             B1=[H1(1:L-1,9);H1(L+1:len,9)];
             C1=H1(L,1:8);
             D1=H1(L,9);


     end


max_ev =7;  %选择主元个数


[COEFF,SCORE,latent,tsquare]=princomp(A1);
A2=A1*COEFF(:,1:max_ev);
C2=C1*COEFF(:,1:max_ev);

    P=A2';
    T=B1';
    %     net=newrb
    %     [net,tr]=newrb(P,T,0.5,2);
    net=newrb(P,T,0.5,2);
    P=C2';
    y=sim(net,P);
    y=y';

       y= y*delta+delta1;      
       x=abs(H2(L)-y)/H2(L);
      
      if k==1
          Y=y;
          X=x;
          D=D1;
          k=0;
      else
          Y=[Y;y];
          X=[X;x];
          D=[D;D1];
      end
      

 end
meanerror=mean(X)
maxerror=max(X)
stderror=std(X)
% 
% X=abs(D1-y);
% error1=sqrt(sum(X.^2)/test_num)
% error2=max(abs(D1-y))
% 
%  y= y*(max(H2)-min(H2))+min(H2);
% T=[1:1:20]';
% V=[1,20,-0.5,1.5];
% plot(X,'r--','LineWidth',2 );
plot(H2,'r--','LineWidth',2 );
% axis(V)
hold on
plot(Y,'b','linewidth',2);