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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 4 g+ n4 S2 t( a9 x, @0 z, J5 T% m% p) j
40 25 3. 6.5 10 ! ^! o4 F {; t
40 30 3.5 7. 20 ' u2 t7 ] }9 r( m, }% y
45 21 2.5 6.5 10
7 ?0 v. M! h7 o, D" L. O 45 25 3. 7. 20 3 v, {9 O$ K) v a4 r
45 30 3.5 6. 5 * s* E3 Q! r! b c) J% \. [0 f! ~5 E
50 21 3. 6. 20
( j( E l2 [% ^4 ~3 l3 V. | z 50 25 3.5 6.5 5
/ A0 f4 k: X6 }* V 50 30 2.5 7. 10 : W" }$ U/ [8 C. h/ u5 M% N/ T
40 21 3.5 7. 10
& G+ }7 z J5 T1 L! e+ m 40 25 2.5 6. 20 # u7 G7 p8 H, J5 ?+ h$ ]
40 30 3. 6.5 5
* I4 n! P& t! B! {) F 45 21 3. 7. 5
! J( @" p o" P& d5 {- [' h5 j; p 45 25 3.5 6. 10
" g0 ]; d. L( D! k3 N$ ` 45 30 2.5 6.5 20 - Z" k* r2 h1 i& O7 H! z" g
50 21 3.5 6.5 20
5 \; K) d! Y' V9 j" {# j! O$ | 50 25 2.5 7. 5 $ g Y7 @) J' A" e* u( ]5 q, T
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];/ \& `% x1 K5 \3 Z
T=t';
- b. X4 Z* E6 }& b5 `6 vP=p';
, }4 t2 P, [- ynet=newff(minmax(P),[12,1],{'tansig','purelin'},'trainlm');
( O7 u3 C* l4 H0 [; X7 }" h%训练网络 net.trainParam.show=10;- m. s7 d: |$ M* T4 C4 f
%net.trainParam.lr=0.05;2 k- e, ~9 R$ @' [! N
%net.trainParam.lr_inc=1.05;2 z2 p3 I& }1 W
net.trainParam.epochs=10000;
$ f6 E) m. U' R- ynet.trainParam.goal=1e-5; $ u) V& c' S& T2 e
% randn('seed',192736547);3 f& y& a6 E5 L4 }+ C/ z! ~
% net=init(net);, t: N+ a! c/ h; b; n% j0 |: u, D
[net,tr]=train(net,P,T);
5 P9 P0 ` y8 [: Cminmax_var=minmax(P);
5 j6 M* g C; ]. dminmax_target=minmax(T);
5 h m8 a3 _1 E2 } Usave('result','net','minmax_var','minmax_target'); % 将网络输 转换成
2 Y- Q) p7 b- F3 B0 H / @7 ~0 K6 d( b d# C
load('result');; l: j1 O* |; Y; S; ], f f4 i
[Pnew,endPop,bestSols,trace]=ga(minmax(P),'fitness');
3 B# U9 b5 A9 S4 j4 i. t 2 ^4 f, F9 e: B2 {' W. F/ l: g
%性能跟踪% W2 Z) B8 _' a; n3 I
plot(trace(:,1),trace(:,3),'y-');% O( Z' i" G' S2 ^, u' l
hold on
: o8 R6 A1 L' e" V- h5 m plot(trace(:,1),trace(:,2),'r-');* u6 w8 Q h; l3 s
xlabel('Generation');* g# b4 p) U9 O' D+ A
ylabel('Fitness');
. r7 n3 I6 h9 X legend('change of solution','average change of population');
: ^; u1 }7 y. m- K+ t1 R9 fTRAINLM, Epoch 0/10000, MSE 12.2801/1e-005, Gradient 1739.63/1e-010
5 l7 B- t: z9 s1 hTRAINLM, Epoch 10/10000, MSE 0.694955/1e-005, Gradient 93.6508/1e-010
6 j& D" F' h7 C/ A9 cTRAINLM, Epoch 20/10000, MSE 0.0242391/1e-005, Gradient 2.89095/1e-010
& `! c6 A# q, ?% H3 m) XTRAINLM, Epoch 30/10000, MSE 0.0206875/1e-005, Gradient 4.2655/1e-010+ s9 E/ v4 ]; H
TRAINLM, Epoch 40/10000, MSE 0.0185878/1e-005, Gradient 18.249/1e-010 y. G/ o4 ^8 K: q
TRAINLM, Epoch 50/10000, MSE 0.00947447/1e-005, Gradient 55.0854/1e-010% O2 p: k% _ D" Y# x. P
TRAINLM, Epoch 53/10000, MSE 1.24279e-006/1e-005, Gradient 0.504667/1e-0103 ]# Z) c/ ]& E& @* V
TRAINLM, Performance goal met. ??? Undefined function or variable 'minmax_target'. Error in ==> D:\MATLAB6p5p1\work\fitness.m
5 A2 z9 B( l& |7 F* B/ QOn line 2 ==> min_target=minmax_target(1); Error in ==> D:\MATLAB6p5p1\work\initializega.m. I$ ^. M% i# |, @" q0 a6 H
On line 41 ==> eval(estr); Error in ==> D:\MATLAB6p5p1\work\ga.m: U X" V/ {; m! x- `8 O5 i
On line 148 ==> startPop=initializega(80,bounds,evalFN,evalOps,opts(1:2));% T4 [9 H: L/ J1 o' N5 S8 \8 A" u
所使用的适应度函数是 function [sol,eval]=fitness(P,options)
0 S- |; `2 z8 E2 c1 y1 K min_target=minmax_target(1);
, I! k5 I: ]6 X0 B max_target=minmax_target(2);6 M. j; h5 f( P3 h
eval=sim(net,P)
% ]9 ]* v$ U: \1 w; P& Q8 X$ p; Z if isformax
& ~3 @! \9 X- _4 \+ H. M eval=eval-min_target+(max_target-min_target);; b4 \) D7 }' p l
else
) e. z% k$ m+ {! Q6 v: K6 t5 s; R: R eval=-eval+max_target+(max_target-min_target); _# ?+ I' N) i9 T2 z4 u
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
