工作日d1.txt

小波神经网络对短期电力负荷的预测

P=[0.62479264	0.694970738	0.4223759	0.714660435	0.57829504	0.412450002	0.880426087	0	1	0.846427519	0.172813776	0.711805819	0.0994;
0.682943098	0.796798236	0.349262268	0.780665596	0.608242225	0.381367779	0.958120641	0	1	0.974544859	0.095222118	0.795583994	0.0986;
0.611524823	0.678268053	0.152018859	0.905182141	0.138160864	0.89763862	0.322421019	0	1	0.751712605	0.079746937	0.653151193	0.0988;
0.547357644	0.833315906	0	0.951727443	0.267411667	0.122646277	1	0.168849388	0.63544199	0.440032675	0.476902104	0.54944016	0.0979]';
T=[0.682943098	0.796798236	0.349262268	0.780665596	0.608242225	0.381367779	0.958120641	0	1	0.974544859	0.095222118	0.795583994;
0.611524823	0.678268053	0.152018859	0.905182141	0.138160864	0.89763862	0.322421019	0	1	0.751712605	0.079746937	0.653151193;
0.547357644	0.833315906	0	0.951727443	0.267411667	0.122646277	1	0.168849388	0.63544199	0.440032675	0.476902104	0.54944016;
0.497327345	0.56294602	0.187848291	1	0.04452577	0.283040838	0.868307965	0	0.772269816	0.454452854	0.350031883	0.472289501]';
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=[0.497327345
	0.56294602
	0.187848291
	1
	0.04452577
	0.283040838
	0.868307965
	0
	0.772269816
	0.454452854
	0.350031883
	0.472289501
	0.0960];
Out1=sim(net,P_test1);

P_test2=[0.531694126
	0.822024572
	0.201644418
	0.461481227
	0.727780036
	0.396955013
	0.69266577
	0
	1
	0.4147685
	0.456044643
	0.552674524
	0.0969];
Out2=sim(net,P_test2);

P_test3=[0.639243803
	0.663536273
	0.252606959
	0.704486728
	0.435451584
	0.333568241
	0.7069124
	0.32025513
	0.477386606
	1
	0
	0.698236153
	0.0971];
Out3=sim(net,P_test3);

P_test4=[0.554540511
	0.561898189
	0.346409002
	0.598218095
	0.521633831
	0
	1
	0.149629816
	0.555335257
	0.698929184
	0.207955829
	0.607993475
	0.0973];
Out4=sim(net,P_test4);

P_test5=[0.537534057
	0.799072832
	0.228652759
	0.554345086
	0.693851409
	0
	1
	0.421280143
	0.448326624
	0.467471839
	0.574836322
	0.562604205
	0.0983];
Out5=sim(net,P_test5);