1-6.txt

小波神经网络对短期电力负荷的预测

P=[0.510671927	0.65136697	0.400996333	0.60650008	0.489327276	0.675322812	0.438769329	0.340498964	0.730412084	0.829391838	0.268053563	0.107245337	0.1004;
0.77780966	0.822349753	0.182998565	0.469731388	0.716977523	0.525536824	0.463514267	0.687808863	0.418404272	0.418177108	0.59510601	0.833086243	0.1009;
0.572232983	0.718053563	0.411533557	0.185800255	0.891798183	0.736756735	0.263279133	0.446285669	0.817858282	0.154300175	0.843802806	0.552316276	0.0983;
0.882065997	0.672361709	0.227498804	0.770070142	0.396544715	0.515108401	0.574114857	0.661194803	0.413713534	0.552598039	0.59618205	0.295540411	0.0968]';
T=[0.77780966	0.822349753	0.182998565	0.469731388	0.716977523	0.525536824	0.463514267	0.687808863	0.418404272	0.418177108	0.59510601	0.833086243;
0.572232983	0.718053563	0.411533557	0.185800255	0.891798183	0.736756735	0.263279133	0.446285669	0.817858282	0.154300175	0.843802806	0.552316276;
0.882065997	0.672361709	0.227498804	0.770070142	0.396544715	0.515108401	0.574114857	0.661194803	0.413713534	0.552598039	0.59618205	0.295540411;
0.753487167	0.377841543	0.626263351	0.585824167	0.503059142	0.383369201	0.724964132	0.429523354	0.573188267	0.640411286	0.460832138	0.337693289]';
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=[0.753487167
	0.377841543
	0.626263351
	0.585824167
	0.503059142
	0.383369201
	0.724964132
	0.429523354
	0.573188267
	0.640411286
	0.460832138
	0.337693289
	0.0996];
Out=sim(net,P_test);