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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
/ D; z# [1 x* i. f0 ?( l+ Y/ L 40 25 3. 6.5 10
1 W' _( `0 z% V, M 40 30 3.5 7. 20
' X( O0 G) Z( y 45 21 2.5 6.5 10 * Q$ F. F) ?. B
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50 25 3.5 6.5 5
7 h- u" \8 @+ W2 w/ s% B 50 30 2.5 7. 10 5 l0 K1 `7 W0 a+ x4 G" O; x
40 21 3.5 7. 10 7 ]9 _0 q' i2 Y
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40 30 3. 6.5 5
! l0 u& d* j9 @7 R7 A 45 21 3. 7. 5 9 L+ C* O) L2 ?
45 25 3.5 6. 10 0 j; e, s C1 I: `3 o. |
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, ]+ p- n; g6 v7 z' I$ U( L 50 21 3.5 6.5 20 3 ~# u P( q1 q1 q7 o( V. |
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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];
+ u. l7 R; g: I& l9 I; D( _T=t';7 X- f; s( T$ v3 ^
P=p';
3 m* x, ]( @1 N7 O# E0 z. e7 L2 [net=newff(minmax(P),[12,1],{'tansig','purelin'},'trainlm');
, Z% i5 T# i5 \/ {, _1 v%训练网络 net.trainParam.show=10;/ b4 x g- h. {: _1 S0 o! p( j
%net.trainParam.lr=0.05;
& m6 M2 F7 n1 @( ^%net.trainParam.lr_inc=1.05;7 y/ o) v0 |" d1 ~0 s
net.trainParam.epochs=10000;
6 Y, h( K# f& A7 V2 ]2 H: s" a3 Vnet.trainParam.goal=1e-5; 7 E) @3 J r- {2 j- i! u5 C
% randn('seed',192736547);3 h7 i# p7 W, x$ o" o
% net=init(net);
/ O7 {, {# Y q$ q( k[net,tr]=train(net,P,T);
" V; e' f+ D1 T& U- fminmax_var=minmax(P);( J: e5 k; Q# w5 y% Q- C
minmax_target=minmax(T);
" \1 B# ~+ a+ X3 _/ }# r* {) n/ tsave('result','net','minmax_var','minmax_target'); % 将网络输 转换成
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2 m2 ]* G& t3 V' @; ^& C# `3 Q load('result');' E2 ^& h. G/ l# Z' e" n
[Pnew,endPop,bestSols,trace]=ga(minmax(P),'fitness');
6 L: ^% o' H2 A) n2 u! _
5 p3 p& N4 B7 |3 z" T9 H %性能跟踪# T# H2 x1 ^! S2 h5 Y/ R! e% b1 f
plot(trace(:,1),trace(:,3),'y-');
; ]. r. ~ b) _: h: v hold on
6 o& s/ Z9 z' l Z plot(trace(:,1),trace(:,2),'r-');
4 l$ _9 q" h) o7 n$ ^, r! w4 b# P xlabel('Generation');
2 L( F( r$ r/ R- }5 P. ^ ylabel('Fitness');" o* x4 n+ J7 c. g. }
legend('change of solution','average change of population');
; q/ c6 S* H. O$ U0 x T9 LTRAINLM, Epoch 0/10000, MSE 12.2801/1e-005, Gradient 1739.63/1e-010 X9 t a5 I" S- `; q
TRAINLM, Epoch 10/10000, MSE 0.694955/1e-005, Gradient 93.6508/1e-010
/ U3 u# o6 S ]3 b7 _! eTRAINLM, Epoch 20/10000, MSE 0.0242391/1e-005, Gradient 2.89095/1e-010
4 w) x4 W5 o) ^" E) S6 }TRAINLM, Epoch 30/10000, MSE 0.0206875/1e-005, Gradient 4.2655/1e-0109 L+ L8 K2 j K8 |0 U& R
TRAINLM, Epoch 40/10000, MSE 0.0185878/1e-005, Gradient 18.249/1e-010
; O9 z: K8 j/ O- f" gTRAINLM, Epoch 50/10000, MSE 0.00947447/1e-005, Gradient 55.0854/1e-010
! A* G2 [) Y4 ^! I8 `: f0 aTRAINLM, Epoch 53/10000, MSE 1.24279e-006/1e-005, Gradient 0.504667/1e-0101 h* f7 H7 s, v- s
TRAINLM, Performance goal met. ??? Undefined function or variable 'minmax_target'. Error in ==> D:\MATLAB6p5p1\work\fitness.m
3 G+ V4 h$ F( e6 d" Z `4 \6 {On line 2 ==> min_target=minmax_target(1); Error in ==> D:\MATLAB6p5p1\work\initializega.m; a& B$ Z4 J3 \. O+ t% Z9 H, ]9 r0 E
On line 41 ==> eval(estr); Error in ==> D:\MATLAB6p5p1\work\ga.m$ T: f |6 f. o. H, X; }
On line 148 ==> startPop=initializega(80,bounds,evalFN,evalOps,opts(1:2));& s2 P4 C1 L' Q# l, |6 s% z
所使用的适应度函数是 function [sol,eval]=fitness(P,options)$ l: F4 x/ h8 Y6 Z# x
min_target=minmax_target(1);: W: q1 ]9 j3 G. ]% l
max_target=minmax_target(2);! S0 t2 ]3 X9 q1 t) s) [) |# d e x
eval=sim(net,P)
E3 C0 ?, x, V if isformax/ G0 N- d4 a# G: Y0 E( U
eval=eval-min_target+(max_target-min_target);# i8 N1 L! A7 ~( g; i: }( C" p# d
else
9 C) B. Z3 V; U$ L) `3 N( n eval=-eval+max_target+(max_target-min_target);
( N, ]: x" h$ ?: C0 Y 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
