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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 ( l2 |* i" ~, Q5 P/ ]6 h1 n
40 25 3. 6.5 10
4 q8 }. i8 a# n+ ]$ A- w2 o9 I 40 30 3.5 7. 20
! d+ V$ ?; Z5 t6 I& q 45 21 2.5 6.5 10
1 e0 F6 [1 f; h+ r5 B' ^ 45 25 3. 7. 20
0 ~9 Z/ Q$ r, r4 x5 S' l( t 45 30 3.5 6. 5
5 c9 y8 x" L( W- l2 d6 l 50 21 3. 6. 20
, h! P2 M# h! v* ?+ Q( e* d' L$ h+ b( r 50 25 3.5 6.5 5 : s8 [4 A8 e3 n
50 30 2.5 7. 10
( M( m& {* x/ i$ W 40 21 3.5 7. 10
2 h3 M5 H$ E7 ^: h3 _- m 40 25 2.5 6. 20
4 g6 U% r# @* A6 y* N 40 30 3. 6.5 5 ! _; B" E P9 t+ R5 n/ m4 `
45 21 3. 7. 5
( I" t( Z } N 45 25 3.5 6. 10 8 F! J# p8 @3 W+ O# U
45 30 2.5 6.5 20
+ ~9 t1 v2 x; P3 X5 r 50 21 3.5 6.5 20 : g/ V* ` W2 X4 a- O( I
50 25 2.5 7. 5 4 k+ n) L. @7 z/ p+ T0 V# r
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& H- O2 x( n, u7 L* VT=t';
7 Z }& t! p6 r( u6 j/ y) J K& XP=p';
: }! @" A. M: j) M- ~net=newff(minmax(P),[12,1],{'tansig','purelin'},'trainlm');& ]# \- z& X( T1 d3 _& W
%训练网络 net.trainParam.show=10;
+ V- C. |# R i: [; C%net.trainParam.lr=0.05;8 G$ p z% Y" @
%net.trainParam.lr_inc=1.05;- `5 ~ x# I5 a% Y I, ^
net.trainParam.epochs=10000;
* O( C* V9 q4 I2 M+ enet.trainParam.goal=1e-5;
& o2 l( t2 d C0 }; D% g* x% randn('seed',192736547);4 r& ^5 I4 f" S' E0 k
% net=init(net);# p6 e1 m! N, t! i+ U
[net,tr]=train(net,P,T);
1 t- h" O: V# @minmax_var=minmax(P);. d; l* ?9 k% [! i' O, U6 Y: Q' \1 E
minmax_target=minmax(T);' P/ Z9 O3 n. W b3 W4 w; l
save('result','net','minmax_var','minmax_target'); % 将网络输 转换成, G/ z+ J& A' D( J) l! \
6 d. G8 A8 x1 W, r load('result');
" K0 `0 [- M% E% b* ^7 ~8 z0 e6 @ [Pnew,endPop,bestSols,trace]=ga(minmax(P),'fitness');
4 L) h& Q" V& p. e3 c & D; K X0 |% P0 p5 F% M# T
%性能跟踪' A [% ^3 ^. I; {
plot(trace(:,1),trace(:,3),'y-');+ i% m' C" K1 H# F1 D& a( @2 X
hold on
+ M- d& z3 V. L V; l plot(trace(:,1),trace(:,2),'r-');
. ]' P9 z3 B, c' o" m, \0 E: G2 q xlabel('Generation');0 a/ E4 o/ q+ b
ylabel('Fitness');: {2 ~& ]- u/ d# h
legend('change of solution','average change of population');
5 S' l# e3 B6 @* V. P% g$ sTRAINLM, Epoch 0/10000, MSE 12.2801/1e-005, Gradient 1739.63/1e-0107 @% L$ k( v+ W5 y; Z m/ f
TRAINLM, Epoch 10/10000, MSE 0.694955/1e-005, Gradient 93.6508/1e-010
* K/ S# t9 ]1 q4 \TRAINLM, Epoch 20/10000, MSE 0.0242391/1e-005, Gradient 2.89095/1e-010
' R A x: S. Q* Q8 @TRAINLM, Epoch 30/10000, MSE 0.0206875/1e-005, Gradient 4.2655/1e-010
( v" K6 E7 }1 }! x& e/ PTRAINLM, Epoch 40/10000, MSE 0.0185878/1e-005, Gradient 18.249/1e-0109 Y6 J0 M# W8 N4 e1 L
TRAINLM, Epoch 50/10000, MSE 0.00947447/1e-005, Gradient 55.0854/1e-010 v; ]' O0 K4 _+ F, J
TRAINLM, Epoch 53/10000, MSE 1.24279e-006/1e-005, Gradient 0.504667/1e-010
+ F& u) |" u" F4 E' M( `4 p% k- MTRAINLM, Performance goal met. ??? Undefined function or variable 'minmax_target'. Error in ==> D:\MATLAB6p5p1\work\fitness.m
! R# h1 o9 \, |. a# TOn line 2 ==> min_target=minmax_target(1); Error in ==> D:\MATLAB6p5p1\work\initializega.m! h: m) a( |- Z5 M
On line 41 ==> eval(estr); Error in ==> D:\MATLAB6p5p1\work\ga.m& X3 K$ m5 a6 R6 j! ?
On line 148 ==> startPop=initializega(80,bounds,evalFN,evalOps,opts(1:2));
. s6 d) D0 o6 C/ g6 P. y* \$ M; S所使用的适应度函数是 function [sol,eval]=fitness(P,options)/ s( p/ l+ X! f, R- d
min_target=minmax_target(1);! t( A2 g; [/ s5 T% u: T
max_target=minmax_target(2);
+ B1 Z1 z) g4 p2 k7 g, c. o7 u9 h eval=sim(net,P)1 L) Y* O1 q' @$ }
if isformax
; U+ M$ T3 ~+ U) W3 v4 e( [( J eval=eval-min_target+(max_target-min_target);7 F- y) }/ K5 s+ L& T4 C E a
else
* n3 m9 P2 t% F: f e eval=-eval+max_target+(max_target-min_target);; _; ^7 C4 Q* y5 K0 |! \
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
