周末d3.txt

小波神经网络对短期电力负荷的预测

P=[1	0.310200488	0	0.181183961	0.295617719	0.528491601	0.673988418	0.664990517	0.751347873	0.871234083	0.900978732	0.859641696	0.0999;
0.803701136	0.22305026	0	0.214769883	0.438340073	0.82976892	1	0.882977085	0.796564606	0.633916811	0.564808396	0.631975737	0.0970]';
T=[0.803701136	0.22305026	0	0.214769883	0.438340073	0.82976892	1	0.882977085	0.796564606	0.633916811	0.564808396	0.631975737;
0.942937867	0.271625337	0	0.225839409	0.438403421	0.820425822	1	0.904180646	0.861680457	0.768733761	0.722657413	0.763212331]';
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_test1=[0.942937867
	0.271625337
	0
	0.225839409
	0.438403421
	0.820425822
	1
	0.904180646
	0.861680457
	0.768733761
	0.722657413
	0.763212331
	0.0978];
Out1=sim(net,P_test1);

P_test2=[0.786915925
	0.217096525
	0
	0.214003925
	0.439030192
	0.83140971
	1
	0.879348968
	0.786247844
	0.613335844
	0.540959102
	0.612378328
	0.0922];
Out2=sim(net,P_test2);