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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
8 H1 X# I9 W+ N1 f 40 25 3. 6.5 10 ' P+ ?0 t% L. b8 h
40 30 3.5 7. 20 5 S0 O3 |, n3 \) e( T' }
45 21 2.5 6.5 10 2 I8 B! d* u! d, M
45 25 3. 7. 20 " K' u1 Q% [* y. q/ I- j
45 30 3.5 6. 5 A! c5 C3 c$ v) {8 v6 M1 A9 i: R
50 21 3. 6. 20
- l" D" q# g# V$ Q+ @/ q 50 25 3.5 6.5 5
! r4 Y# N, @9 b& U/ D) c2 C 50 30 2.5 7. 10 1 q1 t7 |$ i( `) l# P
40 21 3.5 7. 10
8 V* c. F- F- |, ?2 U- `& y8 h 40 25 2.5 6. 20
( ]9 Q& |6 s& _) K+ o" m8 b 40 30 3. 6.5 5
- m1 d: W: O1 I0 r/ I' i 45 21 3. 7. 5 6 s$ [0 j' L& s' {: g: I, ?
45 25 3.5 6. 10 # G/ A& B- O$ j4 W" G/ E' A
45 30 2.5 6.5 20
4 S* L, f% m$ H( B* _% ? @ 50 21 3.5 6.5 20 + M; l/ W) E/ ^5 s; \. D/ ^
50 25 2.5 7. 5 + B7 M$ V- c% Z3 f2 I
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];
) q+ X: ^1 z& v* V* Q& c) xT=t';* R: r/ ^& W M+ V6 N5 ^2 w# b
P=p';( x" K, Q5 p6 c8 I9 X* } Z
net=newff(minmax(P),[12,1],{'tansig','purelin'},'trainlm');
$ `+ ?+ d% L; `: ?# r, o6 h%训练网络 net.trainParam.show=10;( ^# h; x5 d+ X% z6 O
%net.trainParam.lr=0.05;
, N+ d7 h% d8 ^& P3 l1 ]%net.trainParam.lr_inc=1.05;
2 g9 f) }+ t1 |0 W/ T+ Z/ bnet.trainParam.epochs=10000;
/ R. G7 v" J& \6 }, xnet.trainParam.goal=1e-5;
u) C$ N# ?& Q6 i' M- y- l! u% randn('seed',192736547);/ J/ l1 f$ u3 i: |, J' c9 o
% net=init(net);
+ l( e7 r8 C- N6 M[net,tr]=train(net,P,T);
! I9 s7 v4 s$ `& eminmax_var=minmax(P);
- [8 _: k. M" Y& Y9 sminmax_target=minmax(T);* V7 E2 ]7 M, D
save('result','net','minmax_var','minmax_target'); % 将网络输 转换成
2 {6 C3 Y0 }9 v2 }& Q: O" m: A- } 2 z2 _# {# H9 T6 c8 `
load('result');5 E: J8 O. ^* g9 [! g4 c" u
[Pnew,endPop,bestSols,trace]=ga(minmax(P),'fitness');% z7 j9 Q0 J, R p- L" I$ Z/ C
0 D0 K) f( }) H% A: S' n %性能跟踪
8 f8 }8 v! Q6 o/ ] plot(trace(:,1),trace(:,3),'y-');& V4 [" w& ^; j. D) G1 l P1 y! H- @
hold on
( Z: _" q9 k3 x* g- W) @, i plot(trace(:,1),trace(:,2),'r-');$ \5 [7 z8 ~ Z2 h
xlabel('Generation');5 o3 I' z( l9 R H7 F! i
ylabel('Fitness');/ o% O7 \2 Z2 Q3 H
legend('change of solution','average change of population');8 N/ ]- C" Z# v- b1 g3 e
TRAINLM, Epoch 0/10000, MSE 12.2801/1e-005, Gradient 1739.63/1e-010; n! w% G' Q8 L6 j! S" p* J* i
TRAINLM, Epoch 10/10000, MSE 0.694955/1e-005, Gradient 93.6508/1e-010
, Z) c* {0 o' J3 n" ^% xTRAINLM, Epoch 20/10000, MSE 0.0242391/1e-005, Gradient 2.89095/1e-010
' U3 w: @3 ]9 U) S# d. LTRAINLM, Epoch 30/10000, MSE 0.0206875/1e-005, Gradient 4.2655/1e-010- A' N( q; A+ A2 {
TRAINLM, Epoch 40/10000, MSE 0.0185878/1e-005, Gradient 18.249/1e-010
: O4 b+ [) B/ _$ f) V6 wTRAINLM, Epoch 50/10000, MSE 0.00947447/1e-005, Gradient 55.0854/1e-010
4 O. A6 d' y4 ]+ d8 f( \' VTRAINLM, Epoch 53/10000, MSE 1.24279e-006/1e-005, Gradient 0.504667/1e-010
+ h' l, i8 c- ^8 h7 f& U- M& VTRAINLM, Performance goal met. ??? Undefined function or variable 'minmax_target'. Error in ==> D:\MATLAB6p5p1\work\fitness.m
0 D1 ^. h; s0 l0 }6 nOn line 2 ==> min_target=minmax_target(1); Error in ==> D:\MATLAB6p5p1\work\initializega.m
3 ^; Q# D/ L! z- g* hOn line 41 ==> eval(estr); Error in ==> D:\MATLAB6p5p1\work\ga.m% s; S1 \* s. W+ C) X
On line 148 ==> startPop=initializega(80,bounds,evalFN,evalOps,opts(1:2));8 W; F9 @% b! W* T- h2 C
所使用的适应度函数是 function [sol,eval]=fitness(P,options)0 K& [. T" d4 l4 C: [+ ~
min_target=minmax_target(1);# r$ j. L) g2 {5 ^. O- R
max_target=minmax_target(2);
5 H9 |1 d1 W8 V8 X+ q: E+ y2 C eval=sim(net,P)# @3 @! J2 a: e8 t, y
if isformax
* e) t6 P: H! v8 h) m eval=eval-min_target+(max_target-min_target);
' H+ Y* I- c8 j) c! S+ `/ U/ K( D else" I: D' |1 p" I- i# X+ [5 @
eval=-eval+max_target+(max_target-min_target);
6 u4 b1 [5 n' f& p: D/ z 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
