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谢谢 ilikenba 的回复，我是新手，不太明白，研究了半天，编了一点东西，可运行出了问题，帮忙看看是怎么回事，如何修改，谢谢！ p=[ 40 21 2.5 6. 5 3 A* d+ b+ n# k* e& ~6 R
40 25 3. 6.5 10 6 Z. o- ?' n: Z
40 30 3.5 7. 20
6 u, E. k1 r s3 V! X4 O 45 21 2.5 6.5 10
7 ^% G3 s* d3 t" {& ?' D 45 25 3. 7. 20 9 c0 j* a Z$ X$ J" W3 O j
45 30 3.5 6. 5 # K" S( i! W. J2 @
50 21 3. 6. 20
) g) y1 q! O2 m, V1 y5 m 50 25 3.5 6.5 5
; Z& E, ^- M' b8 V) I 50 30 2.5 7. 10
7 z; R* F4 X- t 40 21 3.5 7. 10 2 \+ f) U; k. G( {- s
40 25 2.5 6. 20 & o" J/ b* d- z2 i' _- s: ^
40 30 3. 6.5 5
+ o# x1 b" H: N/ c7 L 45 21 3. 7. 5
( N) f, n9 ~, W' _ 45 25 3.5 6. 10
* c* o* ^* M- {; S 45 30 2.5 6.5 20 3 v* l/ b1 A, @% z) C/ @- F i: v0 B
50 21 3.5 6.5 20
9 R8 R5 A* \& \9 N6 D |- P 50 25 2.5 7. 5 2 P4 t. E. @" d7 s- u: N. b
50 30 3. 6. 10]; t=[2.673;3.412;1.315;2.019;1.996;0.885;9.317;4.484;1.768;5.720;2.316;0.678;1.042;1.492;0.765;8.812;1.204;3.130];
* E' e/ ]4 [- F5 f4 Q* ]T=t';4 `# d6 a1 z6 k9 H1 @
P=p';# s* o, ?3 G9 j; W/ }: B% m
net=newff(minmax(P),[12,1],{'tansig','purelin'},'trainlm');: s3 y/ X6 S6 o) H; G, `+ i
%训练网络 net.trainParam.show=10;
! a" O% z' ` Q%net.trainParam.lr=0.05;
# o1 \6 _' c2 R, z8 r5 c# W%net.trainParam.lr_inc=1.05;+ d% W2 c& W7 O( z0 c
net.trainParam.epochs=10000;/ ]0 s: X! u2 Q4 w3 a! ^+ A- X
net.trainParam.goal=1e-5;
5 L0 [$ T+ u6 w; l2 v' f% randn('seed',192736547);
% S1 J& }+ j4 T+ }2 v% net=init(net);
4 }0 x8 g( E! f3 B/ T$ @" l3 B[net,tr]=train(net,P,T);
2 ]- A5 N- z0 P' m% C2 v. h/ E. x3 ~minmax_var=minmax(P);
2 ^3 A6 t" K) B/ I1 x- A" gminmax_target=minmax(T);6 f2 L% `; h) m2 A' [0 O
save('result','net','minmax_var','minmax_target'); % 将网络输 转换成
( Q! r# N& G K6 ?! l8 u7 L
3 a) V3 \ Q: x# r2 }5 }# x load('result');1 a4 P7 `2 [4 |3 A9 b4 z
[Pnew,endPop,bestSols,trace]=ga(minmax(P),'fitness');" S! k, i4 F" ~: X; I+ `% J
L3 X; j1 v1 Z8 M
%性能跟踪* t! i' W1 X. V
plot(trace(:,1),trace(:,3),'y-');6 D) {5 g. ]% f% B( H# I3 M
hold on + t6 k8 `# h- u. }7 T/ _
plot(trace(:,1),trace(:,2),'r-');" ~" e; y w8 I; N
xlabel('Generation');
! g8 v1 F( K4 T/ i ylabel('Fitness');
" e. R* p. L& r% a/ M! Z% b2 n legend('change of solution','average change of population');
; \& W R3 x* ]TRAINLM, Epoch 0/10000, MSE 12.2801/1e-005, Gradient 1739.63/1e-010
n5 N5 c7 D- ^TRAINLM, Epoch 10/10000, MSE 0.694955/1e-005, Gradient 93.6508/1e-010
, N- P d$ w7 {, _; X/ cTRAINLM, Epoch 20/10000, MSE 0.0242391/1e-005, Gradient 2.89095/1e-010
9 ? g6 J0 b m. ~2 n- iTRAINLM, Epoch 30/10000, MSE 0.0206875/1e-005, Gradient 4.2655/1e-010
. _' {/ ]$ _8 n7 ^: D7 {TRAINLM, Epoch 40/10000, MSE 0.0185878/1e-005, Gradient 18.249/1e-010
* v( T- f% ~+ ?+ [2 E- YTRAINLM, Epoch 50/10000, MSE 0.00947447/1e-005, Gradient 55.0854/1e-010
( c5 P. f, H) S. _4 q' kTRAINLM, Epoch 53/10000, MSE 1.24279e-006/1e-005, Gradient 0.504667/1e-010
: |; v k+ f( q9 L" u0 ]TRAINLM, Performance goal met. ??? Undefined function or variable 'minmax_target'. Error in ==> D:\MATLAB6p5p1\work\fitness.m( K+ i: A# g$ Z! {% J9 O. Z
On line 2 ==> min_target=minmax_target(1); Error in ==> D:\MATLAB6p5p1\work\initializega.m
/ P1 v0 d3 _$ @, mOn line 41 ==> eval(estr); Error in ==> D:\MATLAB6p5p1\work\ga.m
: j2 l0 m b+ Z/ UOn line 148 ==> startPop=initializega(80,bounds,evalFN,evalOps,opts(1:2));
* w; P$ r3 x7 @, E* V' S0 d2 o所使用的适应度函数是 function [sol,eval]=fitness(P,options)
/ a* ]$ e! D5 |; a min_target=minmax_target(1);. Y2 @+ A, i) P7 E. L# d! _* O
max_target=minmax_target(2);. w+ S$ J( I8 g7 J0 G+ _. V
eval=sim(net,P)5 M. J5 z% F3 R( B3 S# J7 E) V
if isformax z4 a9 T# |3 K) M. V- m C, K
eval=eval-min_target+(max_target-min_target);) Z- X: R. F: d: X- e8 K
else* m T* H# S1 r! `* ? s6 l2 z
eval=-eval+max_target+(max_target-min_target);" T& C. i7 w, b- ?, `- S
end | 
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发表于 2005-1-22 22:42
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发表于 2005-1-23 12:26
