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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
' C4 B1 l/ Q) _) ?- Y- o 40 25 3. 6.5 10
: x$ M. R- k, }. Y% P 40 30 3.5 7. 20
, y6 X, U( k) m. _0 F 45 21 2.5 6.5 10
9 e E! g: F$ y 45 25 3. 7. 20
; J5 L) |3 K7 z" n' H 45 30 3.5 6. 5
# V, _) F8 C* p E$ r 50 21 3. 6. 20
% @; i2 V+ o: @$ [- ]' U' Y$ x 50 25 3.5 6.5 5
2 R- D( [( T0 I6 K) g 50 30 2.5 7. 10
5 s. x; m8 p1 x i0 p' z8 k& R8 t 40 21 3.5 7. 10 5 R7 r. ^/ {# I' J! X
40 25 2.5 6. 20
2 ^4 r% |( B. K4 y6 L% Q) b2 Z 40 30 3. 6.5 5
" z: C% Q2 s2 q7 P 45 21 3. 7. 5 ; l# C; K- F, q4 Q/ e0 r
45 25 3.5 6. 10
* E" i# k% \/ \6 L& T8 A 45 30 2.5 6.5 20
% R0 g5 x0 i2 x 50 21 3.5 6.5 20
: E( v: B; K+ m! { 50 25 2.5 7. 5
^# P+ r; F( N3 J" z8 E! S 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];1 Z2 l9 }; I/ U
T=t';
$ p& E& u4 n8 |$ z4 ~1 Q) |P=p';% ~; D: L2 r# q4 I
net=newff(minmax(P),[12,1],{'tansig','purelin'},'trainlm');
# q* j* ^2 o3 F( m) q%训练网络 net.trainParam.show=10;* R5 [1 @4 x! h d9 w) U0 V7 F
%net.trainParam.lr=0.05;) n3 d( G: Y n) k& i) t3 ~
%net.trainParam.lr_inc=1.05;+ {1 @2 G. A1 q% w) [2 g* H
net.trainParam.epochs=10000;+ d! H r5 R- o
net.trainParam.goal=1e-5; 8 b- n$ g( y+ _, I
% randn('seed',192736547);) m, h' d/ M" K. b
% net=init(net);" y3 H, Z; ]# k
[net,tr]=train(net,P,T);& B. d9 K5 n, K" v
minmax_var=minmax(P);' P: @, h3 Z2 Q- Y
minmax_target=minmax(T);
! G7 F# z0 @$ f( Csave('result','net','minmax_var','minmax_target'); % 将网络输 转换成$ F3 j, _* y8 N0 i. t8 e2 f3 N1 N
6 P& L' Q8 ^4 s, X- h6 a4 }8 f load('result');9 U* ~8 @6 ] R+ P) S _+ s i$ {
[Pnew,endPop,bestSols,trace]=ga(minmax(P),'fitness');
: U0 k, q' @# ?
/ z& b& s5 @ ? \# Z %性能跟踪/ G9 c9 w4 q M
plot(trace(:,1),trace(:,3),'y-');
/ \7 z& J$ a" p; K hold on 7 `; ]! k! Q/ N# q+ z
plot(trace(:,1),trace(:,2),'r-');8 ^) A6 H" b5 v5 ]8 Q8 J2 Z
xlabel('Generation');% Y7 ~1 f+ Z6 i; l; C- p
ylabel('Fitness');
! g+ O3 V* N: E legend('change of solution','average change of population');2 E3 K$ S5 T9 Q- b: F' U! \4 ~ w
TRAINLM, Epoch 0/10000, MSE 12.2801/1e-005, Gradient 1739.63/1e-010
: s D) L4 X( s" u: Q' X1 KTRAINLM, Epoch 10/10000, MSE 0.694955/1e-005, Gradient 93.6508/1e-010% Q# @: a! F4 j) m% B
TRAINLM, Epoch 20/10000, MSE 0.0242391/1e-005, Gradient 2.89095/1e-010$ I8 B: n3 w6 C* Z1 }' X& k: b1 {
TRAINLM, Epoch 30/10000, MSE 0.0206875/1e-005, Gradient 4.2655/1e-010
5 J3 E; V9 S; v9 K& i+ W# f0 `TRAINLM, Epoch 40/10000, MSE 0.0185878/1e-005, Gradient 18.249/1e-0106 u0 [, a( J- Z0 X- `; s( L g6 P
TRAINLM, Epoch 50/10000, MSE 0.00947447/1e-005, Gradient 55.0854/1e-010. }. h! ?; U+ a4 `" J A( J
TRAINLM, Epoch 53/10000, MSE 1.24279e-006/1e-005, Gradient 0.504667/1e-010
* \' K7 A& {2 ~( K+ uTRAINLM, Performance goal met. ??? Undefined function or variable 'minmax_target'. Error in ==> D:\MATLAB6p5p1\work\fitness.m* l B7 L- u* y1 F" T9 d# M' l' _
On line 2 ==> min_target=minmax_target(1); Error in ==> D:\MATLAB6p5p1\work\initializega.m
- X& T) A; J K; sOn line 41 ==> eval(estr); Error in ==> D:\MATLAB6p5p1\work\ga.m
" Q0 m6 P' q* D- C& `! ?$ kOn line 148 ==> startPop=initializega(80,bounds,evalFN,evalOps,opts(1:2));
3 X$ t) p! Q, q: m+ Q所使用的适应度函数是 function [sol,eval]=fitness(P,options)
8 s4 x( n4 g/ m( x min_target=minmax_target(1);
1 r# a( a( S0 Y S max_target=minmax_target(2);
2 R: K5 C. K9 V$ G8 N6 T eval=sim(net,P); u8 l% u4 T1 k; j
if isformax
# |- U. O) J9 O5 Q2 @: C2 Y eval=eval-min_target+(max_target-min_target);. Z0 t) R; r) p# r# a% ]
else
5 R A0 h j0 K% D eval=-eval+max_target+(max_target-min_target);
2 s4 T" d1 f: N2 L/ k( H 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
