13-18.txt

小波神经网络对短期电力负荷的预测

P=[0.446272076	0.526978664	0.558459362	0.533706194	0.500631481	0.438784874	0.405167058	0.407112544	0.400078753	0.398725372	0.424314194	0.475227873	0.1004;
0.480701192	0.478989048	0.452786347	0.401143374	0.329497295	0.231606119	0.221484928	0.308767811	0.433666817	0.627251382	0.730840467	0.729484169	0.1009;
0.486390351	0.505433942	0.500877948	0.473718444	0.425906751	0.351081392	0.326185302	0.356102612	0.398079307	0.471809418	0.542678178	0.606571483	0.0983;
0.509294288	0.569979145	0.571462323	0.513185259	0.419887996	0.272688824	0.227245548	0.295760475	0.387275591	0.54222462	0.637110064	0.657294112	0.0968]';
T=[0.480701192	0.478989048	0.452786347	0.401143374	0.329497295	0.231606119	0.221484928	0.308767811	0.433666817	0.627251382	0.730840467	0.729484169;
0.486390351	0.505433942	0.500877948	0.473718444	0.425906751	0.351081392	0.326185302	0.356102612	0.398079307	0.471809418	0.542678178	0.606571483;
0.509294288	0.569979145	0.571462323	0.513185259	0.419887996	0.272688824	0.227245548	0.295760475	0.387275591	0.54222462	0.637110064	0.657294112;
0.493656025	0.689436918	0.74577433	0.645991629	0.505356648	0.269888725	0.17929385	0.259023757	0.348593388	0.510796424	0.604471408	0.607023582]';
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=0.008;
LP.lr=0.1;
net=train(net,P,T);

P_test=[0.493656025
	0.689436918
	0.74577433
	0.645991629
	0.505356648
	0.269888725
	0.17929385
	0.259023757
	0.348593388
	0.510796424
	0.604471408
	0.607023582
	0.0996];
Out=sim(net,P_test);