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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 1 l) |1 {3 P( @* m. [1 n+ P
40 25 3. 6.5 10 ( h5 b0 `2 Q* K' F9 B2 n
40 30 3.5 7. 20
. c# O0 \% i3 \1 _3 {: F O 45 21 2.5 6.5 10 6 o- ^" {; i, K! Y: j/ u& v% o
45 25 3. 7. 20 8 b1 a" j. c. G u/ f
45 30 3.5 6. 5 ; v' C; K+ O9 {" j1 m5 N
50 21 3. 6. 20
. e* t/ ^3 O1 F% J' o) E# J, s" [ 50 25 3.5 6.5 5
/ }( _( Z0 j+ u% f$ f 50 30 2.5 7. 10 ( |% P4 z6 \1 n( L( A" r: E
40 21 3.5 7. 10 + Z n% c& k" Z
40 25 2.5 6. 20 " x$ ~: Y( T6 p+ L
40 30 3. 6.5 5 - C& a, k* h5 L, `+ ^6 o7 g
45 21 3. 7. 5
' f2 s3 z3 H" U6 A/ `! G 45 25 3.5 6. 10 # p. n+ B" y3 U8 \* I
45 30 2.5 6.5 20 4 t' w* j7 F$ @7 x
50 21 3.5 6.5 20 - |4 H% x# e1 B3 w, m
50 25 2.5 7. 5 0 ^1 K$ g5 H. r, E. P+ a6 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];9 z1 }: J v/ H( B+ _+ ?8 l; ]7 N
T=t';4 i; d0 c, W5 s6 N
P=p';' ]' L. G, {7 r h- ~' h3 D" J
net=newff(minmax(P),[12,1],{'tansig','purelin'},'trainlm');
5 ~5 ^! R9 ^! @% r0 W%训练网络 net.trainParam.show=10;; \/ M) D; l# o# }' T
%net.trainParam.lr=0.05;4 \ V- c) Y' ^% k
%net.trainParam.lr_inc=1.05;
! M/ a1 L; K' ~% Xnet.trainParam.epochs=10000;3 D4 K# n8 |% z" M4 V
net.trainParam.goal=1e-5; 6 U$ ]+ H8 N& r. C" G S% A" x6 Y
% randn('seed',192736547);1 t+ }# G3 ^. i0 P4 P0 o5 ^- }
% net=init(net);
U. {+ ^& S6 m9 v[net,tr]=train(net,P,T);
, F5 J \9 {9 i: Fminmax_var=minmax(P);
( a* S! b' i4 z; {7 pminmax_target=minmax(T);
% E$ T) ^ w' y) [6 `' U: Nsave('result','net','minmax_var','minmax_target'); % 将网络输 转换成9 E. h% @; P! Y/ x; t" Y
$ ^6 I1 ^/ s3 t4 w
load('result');% }5 b. p. w/ |
[Pnew,endPop,bestSols,trace]=ga(minmax(P),'fitness');% R# k" ?; G- [ [% x3 B
5 J: Y, q# O: x/ I" K %性能跟踪( s$ v2 m: x# b; D- Z
plot(trace(:,1),trace(:,3),'y-');+ k, A4 X4 ~- }) L4 X4 L2 S# o
hold on ' g. t/ R* y. c
plot(trace(:,1),trace(:,2),'r-');
j' g! G9 M' }- Z z7 V xlabel('Generation');5 k' p+ {9 K+ B1 T4 l7 m1 G
ylabel('Fitness');
8 V$ ?, \6 Q4 n6 B# o legend('change of solution','average change of population');
9 d3 ]1 c1 b7 z, @8 o1 W! D7 d8 iTRAINLM, Epoch 0/10000, MSE 12.2801/1e-005, Gradient 1739.63/1e-010- N- u# n$ B, r# F+ b/ c* l
TRAINLM, Epoch 10/10000, MSE 0.694955/1e-005, Gradient 93.6508/1e-010) W5 J# w& g+ p* Y: _- B7 X. C9 P
TRAINLM, Epoch 20/10000, MSE 0.0242391/1e-005, Gradient 2.89095/1e-010
, v/ G5 H5 L4 N" NTRAINLM, Epoch 30/10000, MSE 0.0206875/1e-005, Gradient 4.2655/1e-010
. Z8 i) a1 V; N8 V8 LTRAINLM, Epoch 40/10000, MSE 0.0185878/1e-005, Gradient 18.249/1e-0107 |4 U) B2 D1 l6 s: h
TRAINLM, Epoch 50/10000, MSE 0.00947447/1e-005, Gradient 55.0854/1e-010& Y9 m9 v3 L2 R. C
TRAINLM, Epoch 53/10000, MSE 1.24279e-006/1e-005, Gradient 0.504667/1e-0109 }) u! n2 R( k1 m$ L8 p3 P
TRAINLM, Performance goal met. ??? Undefined function or variable 'minmax_target'. Error in ==> D:\MATLAB6p5p1\work\fitness.m
- V8 t9 M0 V& ROn line 2 ==> min_target=minmax_target(1); Error in ==> D:\MATLAB6p5p1\work\initializega.m- w# J' y l) q4 ~6 |; T
On line 41 ==> eval(estr); Error in ==> D:\MATLAB6p5p1\work\ga.m( X' U9 C1 i y) D' F
On line 148 ==> startPop=initializega(80,bounds,evalFN,evalOps,opts(1:2));
; w: Q9 K) [+ @3 y4 C5 W所使用的适应度函数是 function [sol,eval]=fitness(P,options)
! q" `: _3 q3 a# k/ U1 B' h! @ min_target=minmax_target(1);" I. q+ t! K% c( u4 D
max_target=minmax_target(2);
$ l, m7 R5 l, R/ K* U1 W" o eval=sim(net,P)! u. w- |) a/ Z* `1 o
if isformax
' V! i/ G. \, w eval=eval-min_target+(max_target-min_target);
2 p! t. \! x& N, e4 j! a else
7 M& I% @) H$ } X eval=-eval+max_target+(max_target-min_target);
+ v8 t8 H$ m4 O/ m7 h3 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
