1-6.txt

小波神经网络对短期电力负荷的预测

P=[0.608804666	0.410912655	0.371359423	0.423151335	0.461867422	0.543367458	0.52743532	0.399099688	0.293465476	0.179094363	0.290982357	0.672608243	0.1004;
0.855030373	0.461918972	0.31907355	0.312994022	0.322173818	0.457984462	0.525770227	0.52968126	0.434764878	0.19027566	0.256368741	0.641869358	0.1009;
0.97855708	0.418381374	0.239296692	0.276870205	0.331905419	0.563888284	0.589426172	0.396531862	0.346216027	0.368506014	0.415975701	0.54463564	0.0983;
0.981751736	0.579706672	0.343691764	0.110312447	0.175657688	0.662702389	0.702388732	0.351027372	0.262111861	0.296708536	0.360306397	0.549989109	0.0968]';
T=[0.855030373	0.461918972	0.31907355	0.312994022	0.322173818	0.457984462	0.525770227	0.52968126	0.434764878	0.19027566	0.256368741	0.641869358;
0.97855708	0.418381374	0.239296692	0.276870205	0.331905419	0.563888284	0.589426172	0.396531862	0.346216027	0.368506014	0.415975701	0.54463564;
0.981751736	0.579706672	0.343691764	0.110312447	0.175657688	0.662702389	0.702388732	0.351027372	0.262111861	0.296708536	0.360306397	0.549989109;
0.941382899	0.452571214	0.280493236	0.259577918	0.31071904	0.573208451	0.597601588	0.387255258	0.332733125	0.356385682	0.395321765	0.508582008]';
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=[0.941382899
	0.452571214
	0.280493236
	0.259577918
	0.31071904
	0.573208451
	0.597601588
	0.387255258
	0.332733125
	0.356385682
	0.395321765
	0.508582008
	0.0996];
Out=sim(net,P_test);