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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
6 `) x% J2 e' E7 @/ \ o 40 25 3. 6.5 10 : {4 \2 p- X3 L9 j2 {9 V& H& D1 s
40 30 3.5 7. 20 1 k; s: i6 X8 B, T
45 21 2.5 6.5 10
# M8 }2 O4 X# m( z5 G; \# m( |8 q 45 25 3. 7. 20
) J2 q- x+ \" [5 h! M! g$ Z2 I 45 30 3.5 6. 5 $ U( }0 s v3 o
50 21 3. 6. 20
! b ?0 A- m* q9 `/ ~7 e 50 25 3.5 6.5 5 # Y1 g. J" t x( r& T
50 30 2.5 7. 10 4 t; e) E% v6 C1 c
40 21 3.5 7. 10
, T# }) g$ Q5 x% C% V- u6 S 40 25 2.5 6. 20
6 J' v( f& \' X+ K 40 30 3. 6.5 5
" M0 _1 d( E! c/ l4 {" i: { 45 21 3. 7. 5 ) i, u. k2 a1 Y2 ]
45 25 3.5 6. 10
- @5 y# I+ O. N& s w 45 30 2.5 6.5 20 8 o/ z1 i1 w% |
50 21 3.5 6.5 20 3 e# N, b1 W+ I2 c; O2 d
50 25 2.5 7. 5 : _3 K2 N& ^: I" D/ n
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];
7 j* E9 I& o4 U5 H+ r4 pT=t';
! Q' B1 ~ Y$ R' d$ AP=p';' a6 H \' P' P3 ^8 y- [& Q) @
net=newff(minmax(P),[12,1],{'tansig','purelin'},'trainlm');
0 m7 p7 |2 l. |+ S%训练网络 net.trainParam.show=10;
! f9 X k* y8 _, t4 r" R$ f. n: r%net.trainParam.lr=0.05;0 f# O6 R4 Z* R+ q* T
%net.trainParam.lr_inc=1.05;% T; _9 }' x C$ Q
net.trainParam.epochs=10000;
# t6 } H: ?7 j/ Jnet.trainParam.goal=1e-5;
4 w$ x- c8 \# A' P2 d% randn('seed',192736547);
' p6 E* y8 n9 |9 b0 {: J5 Z2 S: x% net=init(net);
5 V% Q1 @+ _- u% \$ p) O# ^[net,tr]=train(net,P,T);) L- V. e& E% D, Q$ g5 ~. Z
minmax_var=minmax(P);
. j/ R4 e6 o, B& J8 H/ wminmax_target=minmax(T);
8 J1 u2 n7 { D9 `7 @' d2 Z4 K) ^save('result','net','minmax_var','minmax_target'); % 将网络输 转换成
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load('result');
, r4 E, I& D8 p [Pnew,endPop,bestSols,trace]=ga(minmax(P),'fitness');
7 `, d" t/ r- B4 q" Q- p , N+ ?% b$ ^0 J, k
%性能跟踪
# V7 ~4 Z+ G5 e$ G2 d$ \( c plot(trace(:,1),trace(:,3),'y-');
! R" X" L6 u4 r2 ~, z& }" O! F hold on * N: r' l2 v0 ~
plot(trace(:,1),trace(:,2),'r-');
, B4 e" u( L( T xlabel('Generation');
9 y* L* K( {% x' a ylabel('Fitness');
4 h6 l$ W$ a' {/ E2 S0 G( Q# a legend('change of solution','average change of population');
: D( G3 D' F# r- j% O' mTRAINLM, Epoch 0/10000, MSE 12.2801/1e-005, Gradient 1739.63/1e-010
" e! M! W' C6 M5 uTRAINLM, Epoch 10/10000, MSE 0.694955/1e-005, Gradient 93.6508/1e-010
( ]# a% B4 {# _, zTRAINLM, Epoch 20/10000, MSE 0.0242391/1e-005, Gradient 2.89095/1e-010
+ P% s) Y4 U8 X. j7 KTRAINLM, Epoch 30/10000, MSE 0.0206875/1e-005, Gradient 4.2655/1e-010
- h! T, K! d4 D+ k; s2 ~TRAINLM, Epoch 40/10000, MSE 0.0185878/1e-005, Gradient 18.249/1e-010* I8 }) z3 |0 `) c* S1 H5 ?
TRAINLM, Epoch 50/10000, MSE 0.00947447/1e-005, Gradient 55.0854/1e-0109 s' S A. @8 e. t( \# V2 A$ |% w
TRAINLM, Epoch 53/10000, MSE 1.24279e-006/1e-005, Gradient 0.504667/1e-0103 S% }, |) K; F5 c; b2 {
TRAINLM, Performance goal met. ??? Undefined function or variable 'minmax_target'. Error in ==> D:\MATLAB6p5p1\work\fitness.m
' ?6 t6 i4 z* zOn line 2 ==> min_target=minmax_target(1); Error in ==> D:\MATLAB6p5p1\work\initializega.m% u6 |' {; t" q E
On line 41 ==> eval(estr); Error in ==> D:\MATLAB6p5p1\work\ga.m
% q8 E$ m. ^ ?/ \' ~1 F3 H* OOn line 148 ==> startPop=initializega(80,bounds,evalFN,evalOps,opts(1:2));
# S: {" h) a& S0 r g3 ^9 i8 {- `所使用的适应度函数是 function [sol,eval]=fitness(P,options)/ Q. ^+ X: ~' n, U
min_target=minmax_target(1);' C6 A) C' ]( `" @6 H
max_target=minmax_target(2);& o c. ^" J0 ~: {2 `4 H. r
eval=sim(net,P)
' n0 [& |1 V" Z1 d) ]8 N if isformax1 D2 X( o. ]/ P' f- e
eval=eval-min_target+(max_target-min_target);
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eval=-eval+max_target+(max_target-min_target);
4 w' f$ S. `5 h0 k: Q+ o 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
