7-12.txt

小波神经网络对短期电力负荷的预测

P=[0.790532201	0.67917907	0.481686391	0.08465839	0.108424696	0.593881749	0.659715869	0.4074784	0.375585082	0.431839832	0.433543406	0.446435514	0.1004;
0.729277088	0.586930952	0.444885043	0.192841066	0.215140734	0.556153343	0.590846826	0.383022338	0.396536702	0.542094436	0.510687577	0.352728769	0.1009;
0.549800334	0.425807982	0.396582686	0.42706261	0.442963794	0.479246836	0.475766596	0.423810112	0.388104746	0.355069097	0.393995498	0.522040708	0.0983;
0.668910187	0.719257484	0.537433142	0.057043975	0.112539026	0.70611583	0.726372855	0.291313923	0.247869019	0.438616617	0.472467872	0.462577265	0.0968]';
T=[0.729277088	0.586930952	0.444885043	0.192841066	0.215140734	0.556153343	0.590846826	0.383022338	0.396536702	0.542094436	0.510687577	0.352728769;
0.549800334	0.425807982	0.396582686	0.42706261	0.442963794	0.479246836	0.475766596	0.423810112	0.388104746	0.355069097	0.393995498	0.522040708;
0.668910187	0.719257484	0.537433142	0.057043975	0.112539026	0.70611583	0.726372855	0.291313923	0.247869019	0.438616617	0.472467872	0.462577265;
0.570587381	0.580861105	0.478288439	0.223768726	0.287954694	0.679815581	0.659287495	0.285645829	0.232258767	0.394898231	0.474169268	0.57157482]';
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=[0.570587381
	0.580861105
	0.478288439
	0.223768726
	0.287954694
	0.679815581
	0.659287495
	0.285645829
	0.232258767
	0.394898231
	0.474169268
	0.57157482
	0.0996];
Out=sim(net,P_test);