ann_matlab.m

采用matlab进行数值的逼近

close all
clear
echo on
clc 
%读入数据
p1=[10.45;10.455;10.46;10.465;10.47;10.475;10.48;10.485;10.49;10.495;10.5;10.505;10.51;10.515;10.52;10.525;10.53;10.535	;10.54;10.545	;10.55	;10.555	;10.56	;10.565	;10.57	;10.575	;10.58	;10.585	;10.59	;10.595;	10.6	;10.605	;10.61	;10.615	;10.62	;10.625	;10.63	;10.635	;10.64	;10.645	;10.65	;10.655	;10.66	;10.665	;10.67	;10.675	;10.68	;10.685	;10.69	;10.695	;10.7	;10.705;	10.71;	10.715	;10.72	;10.725	;10.73	;10.735	;10.74	;10.745	;10.75	;10.755;	10.76	;10.765	;10.77	;10.775	;10.78	;10.785	;10.79	;10.795	;10.8	;10.805	;10.81	;10.815	;10.82	;10.825	;10.83	;10.835	;10.84	;10.845	;10.85	;10.855	;10.86	;10.865	;10.87	;10.875	;10.88	;10.885	;10.89	;10.895	;10.9	;10.905	;10.91	;10.915	;10.92	;10.925	;10.93	;10.935	;10.94	;10.945	;10.95	;10.955	;10.96	;10.965	;10.97	;10.975	;10.98	;10.985	;10.99	;10.995;	11	;11.005	;11.01	;11.015	;11.02	;11.025	;11.03	;11.035	;11.04	;11.045	;11.05	;11.055	;11.06	;11.065	;11.07	;11.075	;11.08	;11.085	;11.09	;11.095	;11.1	;11.105	;11.11	;11.115	;11.12	;11.125	;11.13	;11.135	;11.14	;11.145	;11.15	;11.155	;11.16	;11.165	;11.17	;11.175	;11.18	;11.185	;11.19	;11.195	;11.2	;11.205	;11.21	;11.215	;11.22	;11.225	;11.23	;11.235	;11.24	;11.245	;11.25];
t1=[9.3583e-006;1.2632e-005;1.6997e-005;2.2798e-005;3.0483e-005;4.063e-005;5.3984e-005;7.1504e-005;9.4413e-005;0.00012427;0.00016307	;0.00021332	;0.00027819	;0.00036167	;0.00046876	;0.0006057	;0.00078026	;0.0010021	;0.0012831	;0.0016379	;0.0020846	;0.0026453	;0.0033467	;0.0042217	;0.0053097	;0.0066585	;0.0083258	;0.01038	;0.012905	;0.015997	;0.019775	;0.024375	;0.029962	;0.036727	;0.044896	;0.054731	;0.066541	;0.080682	;0.097569	;0.11768	;0.14157	;0.16987	;0.2033	;0.24271	;0.28905	;0.34338	;0.40695	;0.48113	;0.56752	;0.66786	;0.78416	;0.91866	;1.0738	;1.2525	;1.4578	;1.6931	;1.9623	;2.2694	;2.6192;	3.0165	;3.4667	;3.9753	;4.5483	;5.1917	;5.9111;	6.7121	;7.5992;	8.5753	;9.6412;	10.794	;12.027	;13.327	;14.673	;16.036;	17.378;	18.653	;19.806;	20.782	;21.525	;21.992	;22.151;	21.992	;21.525	;20.782	;19.806	;18.653;	17.378	;16.036	;14.673	;13.327	;12.027	;10.794;	9.6412	;8.5753	;7.5992	;6.7121	;5.9111	;5.1917	;4.5483	;3.9753	;3.4667;	3.0165	;2.6192	;2.2694	;1.9623	;1.6931;	1.4578	;1.2525	;1.0738	;0.91866	;0.78416	;0.66786	;0.56752	;0.48113	;0.40695	;0.34338	;0.28905	;0.24271	;0.2033	;0.16987	;0.14157	;0.11768	;0.097569	;0.080682	;0.066541	;0.054731	;0.044896	;0.036727	;0.029962	;0.024375	;0.019775	;0.015997	;0.012905	;0.01038	;0.0083258	;0.0066585	;0.0053097	;0.0042217	;0.0033467	;0.0026453	;0.0020846	;0.0016379	;0.0012831	;0.0010021	;0.00078026;	0.0006057	;0.00046876	;0.00036167	;0.00027819	;0.00021332;	0.00016307	;0.00012427	;9.4413e-005;	7.1504e-005	;5.3984e-005;	4.063e-005	;3.0483e-005	;2.2798e-005;	1.6997e-005;	1.2632e-005	;9.3583e-006];
p=p1';
t=t1';
plot(p,t,'b-');
title('要逼近的函数cmp1(蓝色实线)');
pause
clc
%建立BP网络
n=20;
net=newff(minmax(p),[1,n,1],{'tansig','tansig','purelin'},'trainlm');
y1=sim(net,p);
%figure;
%plot(p,t,'b-',p,y1,'r-'); 
%title('cmp1(蓝线)-未训练(红线)');
pause
clc
%训练网络
net.trainParam.show=50;
net.trainParam.epochs=200000;
net.trainParam.goal=1e-8;
net=train(net,p,t);
pause
clc
%对BP网络进行仿真
y2=sim(net,p);
E=y2-t;
MSE=mse(E)
figure;
plot(p,t,'b-',p,y2,'g-'); 
title('cmp1(蓝线)-训练好(绿色)');
echo off
pause
clc