7-12.txt

小波神经网络对短期电力负荷的预测

P=[0.98067113	0.763522238	0.066754344	0.960585047	0.304439662	0.328295871	0.791371752	0.637107445	0.313912801	0.704826239	0.449274669	0.437753069	0.1004;
0.122110633	0.916778256	0.342826399	0.447812052	0.792463733	0.034034752	0.882882991	0.914749721	0.073688825	0.395217599	0.843786864	0.475729316	0.1009;
0.415144269	0.451574207	0.542310697	0.972421489	0.016339869	0.77118205	0.403550933	0.750848876	0.317989798	0.710306074	0.425306871	0.531061693	0.0983;
0.656930496	0.967878208	0.02052447	0.60680695	0.537597999	0.860186514	0.096285669	0.843053563	0.25608959	1	0.165650407	0.460405707	0.0968]';
T=[0.122110633	0.916778256	0.342826399	0.447812052	0.792463733	0.034034752	0.882882991	0.914749721	0.073688825	0.395217599	0.843786864	0.475729316;
0.415144269	0.451574207	0.542310697	0.972421489	0.016339869	0.77118205	0.403550933	0.750848876	0.317989798	0.710306074	0.425306871	0.531061693;
0.656930496	0.967878208	0.02052447	0.60680695	0.537597999	0.860186514	0.096285669	0.843053563	0.25608959	1	0.165650407	0.460405707;
0.739574366	0.649621393	0.373142834	0.537331349	0.615287741	0.336948031	0.58167942	0.959030767	0	0.961860354	0.309297784	0.299230831]';
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_test=[0.739574366
	0.649621393
	0.373142834
	0.537331349
	0.615287741
	0.336948031
	0.58167942
	0.959030767
	0
	0.961860354
	0.309297784
	0.299230831
	0.0996];
Out=sim(net,P_test);