7-12.txt

bp神经网络对短期电力负荷的预测

P=[0.563218391	0.626436782	0.563218391	0.643678161	0.586206897	0.706896552	0.798850575	0.735632184	0.67816092	0.729885057	0.701149425	0.735632184	0.1004;
0.528735632	0.718390805	0.67816092	0.67816092	0.75862069	0.724137931	0.862068966	0.83908046	0.724137931	0.798850575	0.856321839	0.770114943	0.1009;
0.568965517	0.66091954	0.747126437	0.862068966	0.747126437	0.844827586	0.793103448	0.856321839	0.793103448	0.844827586	0.82183908	0.879310345	0.0983;
0.706896552	0.91954023	0.827586207	0.816091954	0.804597701	0.91954023	0.775862069	0.781609195	0.66091954	0.781609195	0.66091954	0.712643678	0.0968]';
T=[0.528735632	0.718390805	0.67816092	0.67816092	0.75862069	0.724137931	0.862068966	0.83908046	0.724137931	0.798850575	0.856321839	0.770114943;
0.568965517	0.66091954	0.747126437	0.862068966	0.747126437	0.844827586	0.793103448	0.856321839	0.793103448	0.844827586	0.82183908	0.879310345;
0.706896552	0.91954023	0.827586207	0.816091954	0.804597701	0.91954023	0.775862069	0.781609195	0.66091954	0.781609195	0.66091954	0.712643678;
0.603448276	0.695402299	0.695402299	0.683908046	0.718390805	0.747126437	0.764367816	0.729885057	0.557471264	0.701149425	0.632183908	0.701149425]';
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=[0.603448276
	0.695402299
	0.695402299
	0.683908046
	0.718390805
	0.747126437
	0.764367816
	0.729885057
	0.557471264
	0.701149425
	0.632183908
	0.701149425
	0.0996];
Out=sim(net,P_test);