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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 " }/ e6 t1 t+ K8 Z9 m0 v
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, [+ L) r7 H' A$ M9 `; e+ F) ^ 40 30 3.5 7. 20 & {! s( Q, N! k- [0 _
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45 30 3.5 6. 5 : O' _$ n+ j; y& ~) w5 {" c6 x
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2 ^' y, J( C Q9 S: e/ d 50 25 3.5 6.5 5 6 J$ X; l0 a- }) P) t$ O. b
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4 r& K x0 j' E. \! u' s 45 25 3.5 6. 10
; U0 j5 N V$ p& }: V 45 30 2.5 6.5 20
" y7 A7 a; ]; e; h 50 21 3.5 6.5 20
+ h, r! g$ c1 ?$ q; A' Z* d0 r6 A 50 25 2.5 7. 5
2 o8 M* | @4 z1 q 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];
8 e1 J: m1 t* r3 z$ \" vT=t';
/ @0 W+ o8 m" q7 Y# qP=p';4 n5 J" t' ^; `: X
net=newff(minmax(P),[12,1],{'tansig','purelin'},'trainlm');
7 ^' ~6 h8 S. D# _7 B+ [$ R%训练网络 net.trainParam.show=10;( T; @( s0 R4 h0 y2 C- W
%net.trainParam.lr=0.05;
! A5 U0 B8 C) v; u. I9 }# f%net.trainParam.lr_inc=1.05;
f4 {2 o& J1 s& o3 fnet.trainParam.epochs=10000;
1 K; x" W0 \0 Lnet.trainParam.goal=1e-5;
U/ {' r* S7 [8 f% randn('seed',192736547);! z+ `2 E5 R9 i, g4 T/ A4 z9 r/ ]
% net=init(net);
1 T" `" |" K! }1 _! I[net,tr]=train(net,P,T);
: U+ g8 w) U$ f+ ^7 \- ?minmax_var=minmax(P);
( t- d6 ^& X. P3 u4 Z% tminmax_target=minmax(T);9 f: g H% ?; C4 @: l* M L
save('result','net','minmax_var','minmax_target'); % 将网络输 转换成$ t5 }! S6 v' ~& `! z
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load('result');9 @& D5 `5 d$ ~5 X8 Q8 Z: h
[Pnew,endPop,bestSols,trace]=ga(minmax(P),'fitness');
% P7 o) `8 b; ], W7 D
' \5 ]+ P6 G! Z, M %性能跟踪8 b2 W3 q) v0 x9 O0 ^7 y
plot(trace(:,1),trace(:,3),'y-');5 C+ [4 b" _* b
hold on
& { L& ~( a$ o% u; z plot(trace(:,1),trace(:,2),'r-');
+ r5 d% C; M, Z xlabel('Generation');! N3 P% K& M; V" B1 k
ylabel('Fitness');
; c: G- l' e* Q# t$ I) }: c9 |% o1 B legend('change of solution','average change of population');7 V* ]' S% [% R! ^/ N
TRAINLM, Epoch 0/10000, MSE 12.2801/1e-005, Gradient 1739.63/1e-010. t2 V# c8 W1 d+ ~0 j0 Z4 B" j
TRAINLM, Epoch 10/10000, MSE 0.694955/1e-005, Gradient 93.6508/1e-010
1 f M2 r: {" l6 \; W- ?TRAINLM, Epoch 20/10000, MSE 0.0242391/1e-005, Gradient 2.89095/1e-010
2 i& y! p$ O* G4 s! j" r/ L& [ x6 DTRAINLM, Epoch 30/10000, MSE 0.0206875/1e-005, Gradient 4.2655/1e-010+ {; X1 P/ T" }) e' Y
TRAINLM, Epoch 40/10000, MSE 0.0185878/1e-005, Gradient 18.249/1e-010- L0 P/ |+ @3 t; O& O
TRAINLM, Epoch 50/10000, MSE 0.00947447/1e-005, Gradient 55.0854/1e-010 S' _$ u0 m4 n7 c
TRAINLM, Epoch 53/10000, MSE 1.24279e-006/1e-005, Gradient 0.504667/1e-010
6 c+ _( v( j1 ~. z8 E! q! F: @% nTRAINLM, Performance goal met. ??? Undefined function or variable 'minmax_target'. Error in ==> D:\MATLAB6p5p1\work\fitness.m9 V3 I* s4 T1 A- b( K
On line 2 ==> min_target=minmax_target(1); Error in ==> D:\MATLAB6p5p1\work\initializega.m
+ |8 `& }# Y% `/ f1 fOn line 41 ==> eval(estr); Error in ==> D:\MATLAB6p5p1\work\ga.m
/ S1 r9 E9 F( H6 R% tOn line 148 ==> startPop=initializega(80,bounds,evalFN,evalOps,opts(1:2));: l2 i9 K4 y! G! _4 W: U6 q
所使用的适应度函数是 function [sol,eval]=fitness(P,options)
! }# \8 ]: n6 V1 ?5 a min_target=minmax_target(1);2 p7 S4 H- L/ O+ A( r- j+ g; I
max_target=minmax_target(2);
8 h! B- F" u0 n9 O( U( f3 Z6 U eval=sim(net,P)
% q* J F+ G4 O% X( Y' m if isformax
9 K( g3 L p# ~ eval=eval-min_target+(max_target-min_target);) J! b2 `/ y) k; {5 n% m% |8 d, x
else
1 O9 T% f9 C& T/ p eval=-eval+max_target+(max_target-min_target);- t& X2 j/ N. u/ M; W
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
