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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 . x. a" c5 M4 c" { D/ |9 Y
40 25 3. 6.5 10
) R. r, `1 p, R3 | 40 30 3.5 7. 20
0 Q# b* {* r: U: Y$ C/ O! k" _ 45 21 2.5 6.5 10 . G$ w! z0 A' R4 \; f3 L
45 25 3. 7. 20 0 d1 O6 z' f9 U7 \3 e
45 30 3.5 6. 5 ) {& b' r; n5 w" k, ]
50 21 3. 6. 20
# ?( d9 P7 N! @' J 50 25 3.5 6.5 5 2 n! W6 v) M3 C2 _4 g
50 30 2.5 7. 10
. F5 }5 f3 ?5 j 40 21 3.5 7. 10
, I) X _. c& v1 I 40 25 2.5 6. 20 + @6 X8 Q" b- ?5 S1 j
40 30 3. 6.5 5
* ^6 y9 j* p# r0 O p 45 21 3. 7. 5 ' d: i# O( g+ r% \2 d q9 Q% L
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50 25 2.5 7. 5
- M& d- m; A- ~, K& r D1 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];
$ W2 @# T0 T0 E- P5 zT=t'; P) O5 p6 n& ~$ l
P=p';' T' m) H4 J" u4 N
net=newff(minmax(P),[12,1],{'tansig','purelin'},'trainlm');
7 O; r! O) f# E+ C%训练网络 net.trainParam.show=10;
4 _+ _; J x& o4 n/ \%net.trainParam.lr=0.05;
! w: p* P2 l0 r. K5 f; u- h5 m%net.trainParam.lr_inc=1.05;
* @' {% I2 q; @, Q1 U4 C3 Snet.trainParam.epochs=10000;
: V* F: s e: w) D# ~* l) Jnet.trainParam.goal=1e-5;
1 b2 c6 h E' {9 Q" J% randn('seed',192736547);
# p/ ~: @8 v! z+ T% net=init(net);4 Q0 X3 K* o4 x3 |8 ]0 c
[net,tr]=train(net,P,T);6 u: J2 ]/ j$ ^
minmax_var=minmax(P);! s" u5 |7 h" z# R: q& ]! M% d K& X
minmax_target=minmax(T);/ `' e. R; l8 @1 ^& q0 G9 u0 D
save('result','net','minmax_var','minmax_target'); % 将网络输 转换成
8 t' ~5 G% h! d* B 3 S2 N' `7 ]- x8 O* N; o: n
load('result');
' t/ D3 s8 R; v( Z' V7 _7 I2 f [Pnew,endPop,bestSols,trace]=ga(minmax(P),'fitness');
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9 f' O) @, R- o" y %性能跟踪; U [0 l8 A' s+ k5 @: u3 D [1 _
plot(trace(:,1),trace(:,3),'y-');
6 z2 J$ p* I. ?1 p8 l7 h9 F hold on
, H+ V }% c z8 v* \+ [3 I plot(trace(:,1),trace(:,2),'r-');
7 d S: N/ o n# s0 b1 X6 `( \7 ? xlabel('Generation');2 D' B# J6 M: k( g
ylabel('Fitness');7 A- }' i3 E o* a
legend('change of solution','average change of population');
! d$ g0 X0 E3 X. hTRAINLM, Epoch 0/10000, MSE 12.2801/1e-005, Gradient 1739.63/1e-010
6 O0 s C" e# S' o: f" ?TRAINLM, Epoch 10/10000, MSE 0.694955/1e-005, Gradient 93.6508/1e-010
2 J& O& v! e3 P' H' vTRAINLM, Epoch 20/10000, MSE 0.0242391/1e-005, Gradient 2.89095/1e-010/ E" m3 ~: s4 X" j" |
TRAINLM, Epoch 30/10000, MSE 0.0206875/1e-005, Gradient 4.2655/1e-010
; z4 A% ^) } oTRAINLM, Epoch 40/10000, MSE 0.0185878/1e-005, Gradient 18.249/1e-010
, Q2 F7 c, o- {- n R& x5 \TRAINLM, Epoch 50/10000, MSE 0.00947447/1e-005, Gradient 55.0854/1e-010, h% M; @, ^3 U4 A K9 z6 M# K% b. x
TRAINLM, Epoch 53/10000, MSE 1.24279e-006/1e-005, Gradient 0.504667/1e-0108 y+ ~. L9 i! I D7 Q3 B4 L
TRAINLM, Performance goal met. ??? Undefined function or variable 'minmax_target'. Error in ==> D:\MATLAB6p5p1\work\fitness.m
+ {" O$ S/ s' ^, i9 I7 TOn line 2 ==> min_target=minmax_target(1); Error in ==> D:\MATLAB6p5p1\work\initializega.m
' }0 e8 ^! W! U. q2 j4 P0 A2 ~On line 41 ==> eval(estr); Error in ==> D:\MATLAB6p5p1\work\ga.m7 e' }3 x _6 d/ G
On line 148 ==> startPop=initializega(80,bounds,evalFN,evalOps,opts(1:2)); c& B! G+ V6 I7 A2 J, y9 |9 N
所使用的适应度函数是 function [sol,eval]=fitness(P,options)
/ n4 e7 f" G" f min_target=minmax_target(1);9 j6 C" W' c: x
max_target=minmax_target(2);
' J/ W' G/ v c eval=sim(net,P)
2 ]7 ]5 Y6 c5 ]# ?& M4 H( T7 W if isformax
# O9 V# `+ Q5 j/ |2 P% N% N eval=eval-min_target+(max_target-min_target);
8 O0 }$ } y/ k4 ^0 k3 a9 Q else: ?6 F( l ]7 k6 x
eval=-eval+max_target+(max_target-min_target);
7 A3 f! E7 f+ J% z- L, L& q" b 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
