工作日d2.txt

小波神经网络对短期电力负荷的预测

P=[0.526249957	0	0.127275651	0.859366206	0.883670446	0.328532212	0.214166753	0.348031885	0.555145125	1	0.842160275	0.03094311	0.0994;
0.713226408	0.081859887	0.121200033	0.712053126	0.724396053	0.316352032	0.257617534	0.394849292	0.601353967	1	0.816944539	0	0.0986;
0.671871417	0	0.109013161	0.907873619	0.956573577	0.423469528	0.291190902	0.348431696	0.532493007	1	0.876301188	0.133374604	0.0988;
0.709359198	0.089896111	0.117192241	0.669817045	0.699025467	0.36203181	0.289307714	0.335395789	0.537271306	1	0.830357635	0	0.0979]';
T=[0.713226408	0.081859887	0.121200033	0.712053126	0.724396053	0.316352032	0.257617534	0.394849292	0.601353967	1	0.816944539	0;
0.671871417	0	0.109013161	0.907873619	0.956573577	0.423469528	0.291190902	0.348431696	0.532493007	1	0.876301188	0.133374604;
0.709359198	0.089896111	0.117192241	0.669817045	0.699025467	0.36203181	0.289307714	0.335395789	0.537271306	1	0.830357635	0;
1	0	0.015221286	0.829953616	0.870644184	0.392605368	0.316917564	0.432326395	0.590244311	0.92521643	0.800867396	0.177012341]';
threshold=[0 1;0 1;0 1;0 1;0 1;0 1;0 1;0 1;0 1;0 1;0 1;0 1;0 1];
net=newff(threshold,[27,12],{'tansig','logsig'},'trainlm');
net.trainParam.epochs=1000;
net.trainParam.goal=0.01;
LP.lr=0.1;
net=train(net,P,T);

P_test1=[1
	0
	0.015221286
	0.829953616
	0.870644184
	0.392605368
	0.316917564
	0.432326395
	0.590244311
	0.92521643
	0.800867396
	0.177012341
	0.0960];
Out1=sim(net,P_test1);

P_test2=[0.597126118
	0
	0.09171348
	0.790944379
	0.847939822
	0.413716035
	0.277852786
	0.253152349
	0.449483027
	1
	0.866504328
	0.040299443
	0.0969];
Out2=sim(net,P_test2);

P_test3=[0.696274251
	0
	0.073120315
	0.801459418
	0.851679825
	0.40015939
	0.281473364
	0.302567679
	0.496827136
	1
	0.860047817
	0.056869972
	0.0971];
Out3=sim(net,P_test3);

P_test4=[0.66854725
	0.065484586
	0.101188797
	0.664006985
	0.715575257
	0.410642756
	0.307253677
	0.25445631
	0.452605279
	1
	0.849929478
	0
	0.0973];
Out4=sim(net,P_test4);

P_test5=[0.779801232
	0.075223964
	0.070366741
	0.609546473
	0.66975084
	0.434106523
	0.339899216
	0.242231243
	0.435966125
	1
	0.851469765
	0
	0.0983];
Out5=sim(net,P_test5);