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fanfanjia

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Çë¸ßÈËÖ¸µã£¬ÒÔÏÂΪÎÒΪ±ÏÒµÂÛÎÄÉè¼ÆÓÃMATLAB×öµÄBPÉñ¾­ÍøÂ磬Ŀǰ´æÔÚÁ½¸öÎÊÌ⣺
1.Ä£ÐÍÔ¤²â¾«¶ÈÌØ±ðµÍ¡£
ÎÒÒѾ­³¢ÊԸıäÒþº¬²ã½ÚµãÊý£¨´Ó20µ½100¶¼Ò»Ò»ÊÔ¹ýÁË£©£¬²¢½«´«µÝº¯ÊýºÍѵÁ·º¯Êý¶¼×öÁËÌæ»»£¬µ«¾ùÎÞÃ÷ÏÔЧ¹û¡£²»Öª¸Ã´ÓºÎ´¦×ÅÊÖÌá¸ßÄ£Ð͵ÄÔ¤²âºÍѵÁ·¾«¶È¡£
2.ÿ´Î³ÌÐòÔËÐÐÍ꣬¶¼ÒªÌáʾ´íÎó£¬Ã²ËÆÊÇÔËËã·ûºÏ²»¶Ô£¬µ«ÊǸĹýÖ®ºóÒÀÈ»ÓÐÎó¡£²»Öª¸ÃÔõô¸Ä£¿


clc;
clear;
close all;
warning off;
tic;
%ÓÃ2012ÄêÊý¾Ý´´½¨Ä£ÐÍ£¬2011ÄêÊý¾ÝÑé֤ģÐ;«È·¶È¡£ ×Ô¶¯¶ÁÈ¡Îı¾Îĵµ£¬µÚÒ»ÐÐΪũѧ²ÎÊý£¬µÚ¶þÐÐÖÁ×îºóÒ»Ðж¼Îª¹âÆ×Öµ¡£
data1=importdata('E:\2012SR.txt');
data2=importdata('E:\2011SR.txt');

M1 = size(data1,2);%ÐР     
Y1 = data1(1,1:M1);%µÚÒ»ÐÐËùÓÐÁÐ,ũѧ²ÎÊý£¬2012

M2 = size(data2,2);      
Y2 = data2(1,1:M2);%µÚÒ»ÐÐËùÓÐÁУ¬Å©Ñ§²ÎÊý,2011

P =data1(2:size(data1,1),: );      %2012Äê¹âÆ×Êý¾Ý£¬Îı¾ÀïµÚ¶þÐпªÊ¼£¬ËùÓÐÁÐ
T = Y1 ;    %2012Äêũѧ²ÎÊý£¬µÚÒ»ÐÐËùÓÐÁÐ
N2011_validation=data2(2:size(data2,1),: ) ;  %2011Äê¹âÆ×Êý¾Ý£¬Îı¾ÀïµÚ¶þÐпªÊ¼£¬ËùÓÐÁÐ
N2012_data=P;       %2012Äê¹âÆ×Êý¾Ý

net=newff(P,T,[61 1],{'tansig' 'purelin'},'traingd')
t1                      = clock;                              %¼ÆÊ±¿ªÊ¼
net                     = fitnet(70);
net.trainParam.epochs   = 5000;                               %ÉèÖÃѵÁ·´ÎÊý
net.trainParam.goal     = 0.01;                            %ÉèÖÃÐÔÄܺ¯Êý£¨ÑµÁ·ÒªÇ󾫶ȣ©
net.trainParam.show     = 1;                                  %ÿ10ÏÔʾ
net.trainParam.Ir       = 0.005;                              %ÉèÖÃѧϰËÙÂÊ
net                     = train(net,P,T);                  %ѵÁ·BPÍøÂ磨PΪÊäÈ룬TΪÊä³ö£©
datat                   = etime(clock,t1);
Nets                    = net;
view(Nets);

%2011ÄêÊý¾Ý½øÐÐÑéÖ¤
y = sim(net,N2011_validation);
figure;
plot(y,'k-x');hold on
plot(N2011_validation(1:126),'.k');hold on
ymin=-1;
ymax=4;
axis([0 length(N2011_validation) floor(ymin) ceil(ymax)]);
legend('Pridicted values','Measured values');
title('Ä£ÐÍÔ¤²â½á¹û£¬ ÑÌÒ¶Nº¬Á¿');
%2012ÄêÊý¾Ý½øÐвâÊÔ
y1=sim(net,N2012_data);
figure;
plot(y1,'k-x');
hold on;
plot(N2012_data(1:102),'.k');
ymin=0;
ymax=4;
axis([0 length(N2012_data) floor(ymin) ceil(ymax)]);
legend('Pridicted values','Measured values');
title('Ä£ÐÍѵÁ·½á¹û£¬ ÑÌÒ¶Nº¬Á¿');
%µ¼Èëµ½Îı¾Îļþ
fid=fopen('E:\2012SR1.txt','wt');
if fid == -1
    error('Îļþ´ò¿ªÊ§°Ü');
end
fprintf(fid,'ʵ¼ÊÖµ Ô¤²âÖµ\n');
A=[N2012_data;y1];
fprintf(fid,'%f %f\n',A);
fclose(fid);
fid=fopen('E:\2011SR1.txt','wt');
if fid == -1
    error('Îļþ´ò¿ªÊ§°Ü');
end
fprintf(fid,'ʵ¼ÊÖµ Ô¤²âÖµ\n');
A=[N2011_validation;y];
fprintf(fid,'%f %f\n',A);
fclose(fid);
%Ô¤²âЧ¹û·ÖÎö
for i = 1:length(N2011_validation);
    K(i)  = abs(y(i) - N2011_validation(i))/(N2011_validation(i));
end
RMSE = sqrt(sum((y-N2011_validation)*(y-N2011_validation)')/length(N2011_validation))
E= 1-sum((y-N2011_validation)*(y-N2011_validation)')/sum((N2011_validation-mean(N2011_validation))*(N2011_validation-mean(N2011_validation))')
k= average(sum(abs((y-N2011_validation)/(N2011_validation))))
%ѵÁ·Ð§¹û·ÖÎö
for i = 1:length(N2012_data);
    K_1(i)  = average(sum(abs((y1(i)-N2012_data(i))/(N2012_data(i)))));
end
RMSE_1=sqrt(sum((y1-N2012_data)*(y1-N2012_data)')/length(N2012_data))
E_1= 1-sum((y1-N2012_data)*(y1-N2012_data)')/sum((N2012_data-mean(N2012_data))*(N2012_data-mean(N2012_data))')
k_1 = average(sum(abs((y1-N2012_data)/(N2012_data))))


Ô¤²â³öÀ´µÄ½á¹û×ÜÊÇÕûÌ寫¸ß£¬²»ÖªµÀ¸úÎÒûÓнøÐÐÊý¾Ý¹éÒ»»¯ÓÐûÓйØÏµ£¿Èç¹û½øÐÐÊý¾Ý¹éÒ»»¯ºÍ·´¹éÒ»»¯£¬¸ÃÔÚÄĸöµØ·½ÔõôÌí¼Ó³ÌÐòÄØ£¿Çë¸ßÊÖÖ¸½Ì[ Last edited by jjdg on 2013-1-23 at 13:03 ]
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    ±¾ÄÚÈÝÓÉÓû§×ÔÖ÷·¢²¼£¬Èç¹ûÆäÄÚÈÝÉæ¼°µ½ÖªÊ¶²úȨÎÊÌ⣬ÆäÔðÈÎÔÚÓÚÓû§±¾ÈË£¬Èç¶Ô°æÈ¨ÓÐÒìÒ飬ÇëÁªÏµÓÊÏ䣺xiaomuchong@tal.com
  • ¸½¼þ 1 : 2012SR.txt
  • 2012-12-31 17:40:22, 23.52 K
  • ¸½¼þ 2 : 2011SR.txt
  • 2012-12-31 17:40:33, 30.54 K

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fanfanjia

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