13-18.txt

bp神经网络对短期电力负荷的预测

P=[0.82183908	0.913793103	0.890804598	0.804597701	0.908045977	0.873563218	0.82183908	0.902298851	0.890804598	0.862068966	0.862068966	0.804597701	0.1004;
0.787356322	0.862068966	0.833333333	0.706896552	0.735632184	0.66091954	0.545977011	0.747126437	0.793103448	0.82183908	0.862068966	0.752873563	0.1009;
0.91954023	0.959770115	0.925287356	0.833333333	0.833333333	0.735632184	0.787356322	0.850574713	0.908045977	0.798850575	0.856321839	0.850574713	0.0983;
0.804597701	0.879310345	0.856321839	0.718390805	0.787356322	0.747126437	0.718390805	0.879310345	0.879310345	0.965517241	0.913793103	0.890804598	0.0968]';
T=[0.787356322	0.862068966	0.833333333	0.706896552	0.735632184	0.66091954	0.545977011	0.747126437	0.793103448	0.82183908	0.862068966	0.752873563;
0.91954023	0.959770115	0.925287356	0.833333333	0.833333333	0.735632184	0.787356322	0.850574713	0.908045977	0.798850575	0.856321839	0.850574713;
0.804597701	0.879310345	0.856321839	0.718390805	0.787356322	0.747126437	0.718390805	0.879310345	0.879310345	0.965517241	0.913793103	0.890804598;
0.83908046	0.936781609	0.850574713	0.862068966	0.890804598	0.718390805	0.67816092	0.83908046	0.879310345	0.867816092	0.879310345	0.873563218]';
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=[0.83908046
	0.936781609
	0.850574713
	0.862068966
	0.890804598
	0.718390805
	0.67816092
	0.83908046
	0.879310345
	0.867816092
	0.879310345
	0.873563218
	0.0996];
Out=sim(net,P_test);