工作日a3.txt

小波神经网络对短期电力负荷的预测

P=[0	0.137458855	0.277024358	0.416063199	0.606056616	0.835418038	0.96879526	1	0.985516787	0.889005925	0.802764977	0.731270573	0.0994;
0	0.146547315	0.29258312	0.435549872	0.632736573	0.870588235	0.995396419	1	0.948337596	0.798721228	0.655754476	0.524296675	0.0986;
0	0.152179266	0.300911106	0.443240581	0.644915046	0.890421079	1	0.964540754	0.858655504	0.634080276	0.41221374	0.198227038	0.0988;
0.203684573	0.326618457	0.44869146	0.56714876	0.731921488	0.931301653	1	0.928202479	0.786329201	0.529269972	0.265495868	0	0.0979]';
T=[0	0.146547315	0.29258312	0.435549872	0.632736573	0.870588235	0.995396419	1	0.948337596	0.798721228	0.655754476	0.524296675;
0	0.152179266	0.300911106	0.443240581	0.644915046	0.890421079	1	0.964540754	0.858655504	0.634080276	0.41221374	0.198227038;
0.203684573	0.326618457	0.44869146	0.56714876	0.731921488	0.931301653	1	0.928202479	0.786329201	0.529269972	0.265495868	0;
0	0.144406111	0.290783637	0.43666831	0.635124035	0.873993757	0.99819287	1	0.944307541	0.789715788	0.639888287	0.499917858]';
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
	0.144406111
	0.290783637
	0.43666831
	0.635124035
	0.873993757
	0.99819287
	1
	0.944307541
	0.789715788
	0.639888287
	0.499917858
	0.0960];
Out1=sim(net,P_test1);

P_test2=[0
	0.141055341
	0.284684685
	0.428185328
	0.623680824
	0.859459459
	0.987387387
	1
	0.95971686
	0.826383526
	0.7002574
	0.585842986
	0.0969];
Out2=sim(net,P_test2);

P_test3=[0
	0.143889534
	0.290360046
	0.436830559
	0.636082075
	0.876242096
	1
	0.99883856
	0.939476061
	0.779326365
	0.623951478
	0.478255259
	0.0971];
Out3=sim(net,P_test3);

P_test4=[0
	0.142553191
	0.288216039
	0.434369885
	0.632405892
	0.870703764
	0.995908347
	1
	0.947626841
	0.797708674
	0.652864157
	0.518003273
	0.0973];
Out4=sim(net,P_test4);

P_test5=[0
	0.150615901
	0.301511758
	0.449608063
	0.653415454
	0.898656215
	1
	0.945968645
	0.816069429
	0.559350504
	0.299272116
	0.041433371
	0.0983];
Out5=sim(net,P_test5);