数学建模社区-数学中国

标题: BP神经网络程序问题求助 [打印本页]
作者: T-Eric    时间: 2014-7-18 21:13
标题: BP神经网络程序问题求助
这是我从书上打下来的代码，因为书的运行软件版本比较低，我的是Malab2013a的版本，所以我修改了部分程序，但运行出来有问题。请哪位高手帮忙指教和修正一下。谢谢！！
$ m: `: E& `7 Y
' Y- U, Q3 F4 S( r* p3 O. n+ `%原始数据输入
+ `( q$ n8 _& Z1 n2 U2 g$ E2 iclc
3 r( G" B# s' O6 f& ]7 msqrs=[20.55,22.44,25.73,27.13,29.45,30.1,30.96,34.06,36.42,38.09,39.13,39.99,...7 l" o/ ^& t: Z+ |* i
    41.93,44.59,47.30,52.89,55.73,56.76,59.17,60.63];
' l* z8 e/ ~# q% {1 Tsqjdcs=[0.6,0.75,0.85,0.90,1.05,1.35,1.45,1.60,1.70,1.85,2.15,2.20,2.25,2.35,...: l- A0 r" P" R8 R' x( f4 u4 Z- K7 C
    2.5,2.6,2.7,2.85,2.95,3.10];- u& t3 k9 p6 U
sqglmj=[0.09,0.11,0.11,0.14,0.20,0.23,0.23,0.32,0.32,0.34,0.36,0.36,0.38,0.49,...
) P- x( d! J# s/ O$ O    0.56,0.59,0.59,0.67,0.69,0.79];
: I7 _5 F  Z6 H( [! O- M( R, cglkyl=[5126,6217,7730,9145,10460,11387,12353,15750,18304,19836,21024,19490,20433,...
1 z$ w) {1 I4 y/ P    22598,25107,33442,36836,40548,42927,43462];
4 D% u" ?  M% n% `" S9 X* Z" Cglhyl=[1237,1379,1385,1399,1663,1714,1834,4322,8132,8936,11099,11203,10524,11115,...$ E- e( @0 x6 s. i4 w
    13320,16762,18673,20724,20803,21804];* U6 z) H; c7 h% ^$ d% c. h
p=[sqrs;sqjdcs;sqglmj];
  ]* B9 \5 N1 _. ]4 t1 ?/ rt=[glkyl;glhyl];! G3 g/ V5 U: y
% l6 ]( l1 x2 Z! u6 f% \! P0 P
%数据归一化! M6 L# l- T2 ]3 G$ m
[pn,ps1]=mapminmax(p);  ]# x8 C% c* B8 H9 Q6 ~5 Z/ o
[tn,ps2]=mapminmax(t);0 v- y& R7 `% H
dx=[-1,1;-1,1;-1,1];
0 a1 D3 G1 D: d0 X; b% K# w4 Q4 G2 B  p, w$ t3 C
%BP网络训练! a3 ^. f8 d& J: w7 \4 W
net=newff(p,t,[3,7,2],{'tansig','tansig','purelin'},'traingdx');/ E1 ?- f% }4 ^& T9 u) q% G, k
net.trainParam.show=1000;. A% m8 `# n+ T5 l- K
net.trainParam.Lr=0.05;: M. J- V4 L# m) E: k- |
net.trainParam.epochs=50000;
2 k: E7 H3 B. ynet.trainParam.goal=0.65*10^(-3);
1 E2 o! @8 ?) [7 unet=train(net,pn,tn);9 |. F( g9 a' R
7 I- F3 M% K! J2 ]5 o; R
%利用原数据对BP网络仿真8 k) V1 X; r( W% z) ?: _
an=sim(net,pn);/ U* A' A6 c. `
a=mapminmax('reverse',an,ps2);
5 `1 l6 ?8 [% {7 J, Z: Y9 f7 y6 I' W) m( M, z5 h- y4 W- l7 Y: X
%仿真结果与原数据对比测试/ _, S8 U: f' e2 t# [# s, x
x=1990:2009;. p. Q  g5 I* K9 z2 k
newk=a(1,:);
, |, k! M$ _/ O9 Vnewh=a(2,:);$ `+ |- F4 D/ B
figure(2);$ U- L1 {1 Q) X, H9 L
subplot(2,1,1);plot(x,newk,'r-o',x,glkyl,'b--+');
! i  v0 Q4 k( }1 Dlegend('网络输出客运量','实际客运量');3 {; M6 B6 e9 `& ?3 m  n
xlabel('年份');ylabel('货运量、万人');7 p+ Z  S$ H. Q* M1 x% ]; S3 o
title('运用工具箱客运量学习和测试对比图');3 I  [; p0 a1 A& j9 g
subplot(2,1,2);plot(x,newh,'r-o',x,glhyl,'b--+');1 s2 z  K& x5 M9 @# v
legend('网络输出货运量','实际货运量');& {( d6 x, c; L8 l: E
xlabel('年份');ylabel('货运量、万吨');8 O$ e% _2 v( L% P
title('运用工具箱货运量学习和测试对比图');
  ~* Z! H0 G" S4 O, B3 c. d* D' m/ n; j& |, {' F8 N* |
%新数据仿真
* t7 Q. R+ |, _- N4 fpnew=[73.39,75.55  L: [( Z# c" W$ @/ [6 i
    3.9635,4.0975
, C2 ~7 r9 c# \/ N% a9 z    0.9880,1.0268];; J3 g6 _+ r  }2 k; U* _& p
pnewn=mapminmax('apply',pnew,ps1);
7 I' ]2 s3 ]4 Y4 t9 |1 Q3 E/ janewn=sim(net,pnewn);1 F5 s( ?$ i5 o1 b
anew=mapminmax('reverse',anewn,ps2)
% o; }$ s$ V& F
6 ^) l( d( O7 `0 o! |- A

`VCWMZD9E$D~NHRR~AT9B4D.jpg (120.2 KB, 下载次数: 507)

`VCWMZD9E$D~NHRR~AT9B4D.jpg

作者: gancm    时间: 2014-7-19 12:30
看了图我感觉是网络输出后面那几个值太大了，前面基本都是一条水平线了，具体哪里还看不出问题。你把修改的地方说一下看看
作者: 529084167    时间: 2014-7-21 09:35
作者: T-Eric    时间: 2014-7-21 11:58
gancm 发表于 2014-7-19 12:30
" _* s! c/ s- u) x; P看了图我感觉是网络输出后面那几个值太大了，前面基本都是一条水平线了，具体哪里还看不出问题。你把修改的 ...

& j0 S2 S% L( D* Z因为版本更新，Matlab中的Newff命令用法有所改变，原命令为：
( |& G) q0 }8 }/ B9 Jnet=newff(dx,[3,7,2]{'tansig','tansig','purelin'},'traingdx');
* }8 X" A# o, W我修改为：' K5 y$ n/ M  i0 A7 d* x$ A
net=newff(p,t,[3,7,2],{'tansig','tansig','purelin'},'traingdx');! X, Y& q. f( H9 j+ ]
然后有些命令被其他命令替代了，其中有premnmx，postmnmx，tramnmx命令好像被替换了，使用了一个强大的命令mapminmax。原命令为：( ^( B2 p1 f0 F3 w3 |3 G  E6 o
[pn,minp,maxp,tn,mint,maxt]=premnmx(p,t);, a, e: d7 L1 Q" v
a=postmnmx(an,mint,maxt);2 F; R$ X6 S6 g; C: L, d! n. q6 M
pnewn=tramnmx(pnew,minp,maxp);
5 l! }' M9 V; Y% |9 Yanew=postmnmx(anewn,mint,maxt)
. N) n- f6 {( E% ^9 ]4 y我修改为：+ h* q/ |5 g* b! S9 j
[pn,ps1]=mapminmax(p);[tn,ps2]=mapminmax(t);, [9 X+ |9 @6 s* ~# L8 M# `
a=mapminmax('reverse',an,ps2);
/ s, \7 v2 Q8 c" N* }* ~  b( ~pnewn=mapminmax('apply',pnew,ps1);; U3 H: x' O9 r' C! B
anew=mapminmax('reverse',anewn,ps2)
3 u. `+ z1 \$ L
4 K: W" H% o5 X2 _& E# W+ [+ B原程序为：  s) T! k# z, J* i0 t
%原始数据输入& W0 o6 y$ ~7 o7 y- G4 j
clc
( v7 t0 V- H" ^! [sqrs=[20.55,22.44,25.73,27.13,29.45,30.1,30.96,34.06,36.42,38.09,39.13,39.99,...7 o& u+ h2 I& ]- w, R( b) I9 v. M; `
    41.93,44.59,47.30,52.89,55.73,56.76,59.17,60.63];, _" f3 j% [8 K8 n) ^( E$ ~
sqjdcs=[0.6,0.75,0.85,0.90,1.05,1.35,1.45,1.60,1.70,1.85,2.15,2.20,2.25,2.35,...
5 i4 A& r  `' y- P+ p    2.5,2.6,2.7,2.85,2.95,3.10];& K9 J# r4 F4 i( Y
sqglmj=[0.09,0.11,0.11,0.14,0.20,0.23,0.23,0.32,0.32,0.34,0.36,0.36,0.38,0.49,...
. k. Z% _8 z& \$ B# o" Z    0.56,0.59,0.59,0.67,0.69,0.79];! u  J& S2 ]- P  J
glkyl=[5126,6217,7730,9145,10460,11387,12353,15750,18304,19836,21024,19490,20433,...
! y& e2 t$ e! p    22598,25107,33442,36836,40548,42927,43462];
( n2 k( z! Y5 O& W7 E& ?glhyl=[1237,1379,1385,1399,1663,1714,1834,4322,8132,8936,11099,11203,10524,11115,...' A$ o6 Q4 N1 p  L8 _" p. y! v
    13320,16762,18673,20724,20803,21804];1 ^1 I  W0 Q$ _) C3 m3 _
p=[sqrs;sqjdcs;sqglmj];
, j1 R* O2 J4 D4 `- dt=[glkyl;glhyl];
. D) b( p' A( `9 |* _. w* b
& h' i# \. E) Q! a9 _6 ~%数据归一化
2 H! k+ @) }9 u; q5 b. G[pn,minp,maxp,tn,mint,maxt]=premnmx(p,t);. i' i# D2 T! m
dx=[-1,1;-1,1;-1,1];: h' g) ^  R! Q3 e& k

1 q. u# S8 p1 h5 t& Y%BP网络训练
0 B+ T* ]" E' f) {0 L2 @7 fnet=newff(dx,[3,7,2],{'tansig','tansig','purelin'},'traingdx');$ t& C% i$ q, J& t
net.trainParam.show=1000;
: j2 m3 f/ D* P) I: ^* _% ]net.trainParam.Lr=0.05;5 |8 _! R: D5 x/ C6 A6 b
net.trainParam.epochs=50000;8 `" k* W+ G8 F2 y
net.trainParam.goal=0.65*10^(-3);' s; k+ u0 L4 Y% Q: F
net=train(net,pn,tn);
/ q' C3 G/ ~2 o
/ c3 ~0 [" z9 U* {% v' L%利用原数据对BP网络仿真
3 G" w; A4 V' ean=sim(net,pn);4 }9 S) x2 i+ s3 L  p7 r8 M
a=postmnmx(an,mint,maxt);
6 |; ?) y) c: M9 P; O0 N6 [4 z/ p; ?
%仿真结果与原数据对比测试
2 ^0 M' A" h: b: }6 Vx=1990:2009;
! q; M+ |5 x" ?* Q' P9 znewk=a(1,;9 c: |: {: @0 z4 Z8 S4 @
newh=a(2,;* X! {1 v& C. _% q6 O( n* d- h2 r: x
figure(2);3 z/ \. W, R) X+ H4 }
subplot(2,1,1);plot(x,newk,'r-o',x,glkyl,'b--+');
4 p0 |. i0 b; E9 u3 m- r/ Xlegend('网络输出客运量','实际客运量');
9 c4 J( S) J- cxlabel('年份');ylabel('货运量、万人');
. H' W! C0 l9 ntitle('运用工具箱客运量学习和测试对比图');
) B% O" f0 q' |) V+ Psubplot(2,1,2);plot(x,newh,'r-o',x,glhyl,'b--+');' c- \& s5 b1 Y3 k  R' o7 W
legend('网络输出货运量','实际货运量');
, s! g, j8 F: o" Mxlabel('年份');ylabel('货运量、万吨');6 p; ~# j% f9 k! r+ [2 z6 C
title('运用工具箱货运量学习和测试对比图');) L* i: V1 k' g; a0 _

% |. R# K4 R$ S; ]' W- H6 r%新数据仿真- o! q* X% k/ `. M$ h/ s# q0 ]4 F8 i
pnew=[73.39,75.55
. ^( G8 \0 L9 G/ X/ b    3.9635,4.0975
( L) C4 ^8 Q% [0 ~$ j    0.9880,1.0268];+ e6 P9 T. n3 a- N( P1 I4 [
pnewn=tramnmx(pnew,minp,maxp);4 @; e7 e7 K# p8 H* [
anewn=sim(net,pnewn);
5 P4 S' s/ r, y3 A, n) T4 e9 b% Canew=postmnmx(anewn,mint,maxt)
# i; T* u3 S3 H4 K0 U! s
$ V" c' }- T: j修改后程序为：
2 @: P1 Z& p: ?4 r" b%原始数据输入
9 u0 ^4 X1 q$ d. G/ Hclc
0 {/ l* D. L( ysqrs=[20.55,22.44,25.73,27.13,29.45,30.1,30.96,34.06,36.42,38.09,39.13,39.99,...
% C2 t& Y* V3 d; N4 Y, u    41.93,44.59,47.30,52.89,55.73,56.76,59.17,60.63];- W6 e) g; _9 r: E8 R. ]
sqjdcs=[0.6,0.75,0.85,0.90,1.05,1.35,1.45,1.60,1.70,1.85,2.15,2.20,2.25,2.35,...
5 T! B6 c1 H+ d$ d    2.5,2.6,2.7,2.85,2.95,3.10];4 j3 c6 L$ x1 @# K) i( P- N* F" x
sqglmj=[0.09,0.11,0.11,0.14,0.20,0.23,0.23,0.32,0.32,0.34,0.36,0.36,0.38,0.49,...
6 J" X& a5 x! Z    0.56,0.59,0.59,0.67,0.69,0.79];
3 T; h( v9 y/ ?. ^5 N3 Pglkyl=[5126,6217,7730,9145,10460,11387,12353,15750,18304,19836,21024,19490,20433,...
4 m+ V, N- C6 \: }: r) m+ q    22598,25107,33442,36836,40548,42927,43462];/ J! G2 Y$ E6 A
glhyl=[1237,1379,1385,1399,1663,1714,1834,4322,8132,8936,11099,11203,10524,11115,...
+ P7 C! @1 V+ x4 t" f" ^( @7 y    13320,16762,18673,20724,20803,21804];+ g2 A$ e" P5 ]& _
p=[sqrs;sqjdcs;sqglmj];
5 O: ~3 ^; I' I7 It=[glkyl;glhyl];% R& p: `0 c- R1 O

8 z. w* i4 ]& w4 k%数据归一化3 S+ q2 a. N# B  K" @
[pn,ps1]=mapminmax(p);
7 ~; v' @0 a2 Z2 w6 G[tn,ps2]=mapminmax(t);4 L, c6 C' C& D- e1 w

. q+ X; F. E, K5 @* t%BP网络训练
: j/ {/ P& V, t3 Snet=newff(p,t,[3,7,2],{'tansig','tansig','purelin'},'traingdx');
8 w" A. X# x8 Z# q2 lnet.trainParam.show=1000;6 Y( g  F* _% |& L
net.trainParam.Lr=0.05;3 I+ F3 |  Q) f# S3 l
net.trainParam.epochs=50000;
- m; O. n1 Z* C% b5 Dnet.trainParam.goal=0.65*10^(-3);
$ w+ q& e8 U" ~# g6 Q! r. Jnet=train(net,pn,tn);
" r3 `4 h) \* @0 S8 M5 l2 j- w) ?. |7 N8 w
%利用原数据对BP网络仿真
$ z# y: o' `/ Q# R, B# Y8 [: K+ d# g& ~an=sim(net,pn);
' N# S* f: C; @0 O+ [  qa=mapminmax('reverse',an,ps2);6 A" Y3 I3 s/ |* E7 V& Q

  T6 E- t6 q5 N0 Z%仿真结果与原数据对比测试9 \3 l1 e$ f, m8 K1 {* H* M
x=1990:2009;
  W- ?+ x/ C, k! _newk=a(1,;
  j" s0 p! \7 Z, A, t- R8 enewh=a(2,;
+ ]: z& b/ D7 B2 ]. Y3 y9 \. afigure(2);
+ u( P, _- ~; w; jsubplot(2,1,1);plot(x,newk,'r-o',x,glkyl,'b--+');
! U. V! M+ |5 Hlegend('网络输出客运量','实际客运量');
1 A& V3 ^" L& C8 z' g1 U/ n# Y( a9 txlabel('年份');ylabel('货运量、万人');
' ~$ n- b" P3 x6 b7 `title('运用工具箱客运量学习和测试对比图');! D6 y3 F. k! L& q) {# H- g
subplot(2,1,2);plot(x,newh,'r-o',x,glhyl,'b--+');4 z# |2 a& U4 T+ [$ `% D6 K6 G" y
legend('网络输出货运量','实际货运量');8 K/ m& l# u4 @, X" w# o, G3 ^
xlabel('年份');ylabel('货运量、万吨');8 @0 P2 G6 b6 a+ n" I
title('运用工具箱货运量学习和测试对比图');
: C5 R- W( I6 y8 ?
0 ^/ a6 P8 \! J4 a8 @7 j# o%新数据仿真
- @! ^5 X* F8 l# |& Zpnew=[73.39,75.553 @' X, W: A! l5 [
    3.9635,4.0975
3 }9 [1 }. U% g. X! W    0.9880,1.0268];. i6 l1 s4 K3 K/ q; j8 z
pnewn=mapminmax('apply',pnew,ps1);) M' w$ @8 ~: R+ ?4 C
anewn=sim(net,pnewn);# u- d  _8 [& E: O. b* m& I3 `4 Y7 c
anew=mapminmax('reverse',anewn,ps2)3 Y5 q" ]% J: j% b* \
（修改的地方用颜色标记了）* O6 M+ U* z, n8 N6 M
麻烦您帮忙指出其中的问题，万分感谢！
作者: 且生    时间: 2014-7-21 18:05
求书名及页码……
作者: 且生    时间: 2014-7-21 18:20
  1. clc
    , O# N" u" E, y) b, C
  2. sqrs=[20.55,22.44,25.73,27.13,29.45,30.1,30.96,34.06,36.42,38.09,39.13,39.99,...
    2 x6 @, _: s! ?) L3 ]# o: b
  3.     41.93,44.59,47.30,52.89,55.73,56.76,59.17,60.63];
    4 b: F( j4 @' ]% @
  4. sqjdcs=[0.6,0.75,0.85,0.90,1.05,1.35,1.45,1.60,1.70,1.85,2.15,2.20,2.25,2.35,...
      O) |3 a' e( v
  5.     2.5,2.6,2.7,2.85,2.95,3.10];3 L5 O" z/ R7 y+ a
  6. sqglmj=[0.09,0.11,0.11,0.14,0.20,0.23,0.23,0.32,0.32,0.34,0.36,0.36,0.38,0.49,...  c. e9 X. j- Q' p; ]
  7.     0.56,0.59,0.59,0.67,0.69,0.79];0 |" P7 W  ?% b/ p
  8. glkyl=[5126,6217,7730,9145,10460,11387,12353,15750,18304,19836,21024,19490,20433,...& u3 R/ y; L& c0 h# W
  9.      22598,25107,33442,36836,40548,42927,43462];# L1 ^/ A4 `* Y0 }1 ~
  10. glhyl=[1237,1379,1385,1399,1663,1714,1834,4322,8132,8936,11099,11203,10524,11115,...
    ' S$ c" C/ m! C( c/ e1 L8 _
  11.      13320,16762,18673,20724,20803,21804];
    % K$ t! Q' E3 b
  12. p=[sqrs;sqjdcs;sqglmj];4 o( ^4 R( @- V) ^* |
  13. t=[glkyl;glhyl];! a' l. T: h! k3 @1 m
  14. %数据归一化6 |  Q  a, \8 |+ o% \2 h1 N
  15. [pn,ps1]=mapminmax(p);. u4 `/ p: O/ z. Y
  16. [tn,ps2]=mapminmax(t);
    ; a) }8 d/ O+ ?4 u
  17. %dx=[-1,1;-1,1;-1,1];
    + Q9 K+ Q2 u9 o# L
  18. [color=Red] p0=minmax(pn);t0=minmax(tn);[/color]
    5 q1 D, s4 J& B
  19. ) j' X6 Z* B. |$ [2 B! i
  20. %BP网络训练
    6 b$ ^9 S# p6 \+ G. z
  21. [color=Red] net=newff(p0,t0,[3,7,2],{'tansig','tansig','purelin'},'traingdx'); [/color]
    5 \$ X5 x- ^4 L3 d7 ~$ A$ X) L
  22. net.trainParam.show=1000;' Q6 p! @1 ~! P9 v: u# D9 N& a! f0 J3 J
  23. net.trainParam.Lr=0.05;
    & s6 C, K& f2 U' o, o% v  o+ w
  24. net.trainParam.epochs=50000;5 p& z- S, {' {$ G
  25. [color=Red] net.trainParam.goal=0.65*10^(-5);[/color]
    3 c9 j& \2 R5 j' e
  26. net=train(net,pn,tn);
    3 X, P" m6 [. q+ k

  27. 8 C& H  b! ~( [+ D& F/ M
  28. %利用原数据对BP网络仿真3 x4 s" A2 W) o$ s1 f
  29. an=sim(net,pn);
    & N0 y. l: z/ d5 P( `$ S5 a  ~
  30. a=mapminmax('reverse',an,ps2);  {* L2 T4 h. P- o

  31. 7 l0 b- N5 E& q3 u& H2 ?" o
  32. %仿真结果与原数据对比测试
    7 W; T4 n2 Q+ G0 Q; O) M
  33. x=1990:2009;4 O/ j# `: v8 W% o& m5 y5 ~4 Z
  34. newk=a(1,:);( S+ ~) v, L: t0 M4 M- @
  35. newh=a(2,:);. l& N9 N9 \; q' r4 E) j
  36. figure(2);/ L* |0 T7 R3 r2 ~
  37. subplot(2,1,1);plot(x,newk,'r-o',x,glkyl,'b--+');& D$ G4 s  @( p& O
  38. legend('网络输出客运量','实际客运量');
    8 q5 L. e7 M' L- M
  39. xlabel('年份');ylabel('货运量、万人');4 x2 `* x9 g7 b
  40. title('运用工具箱客运量学习和测试对比图');( s7 s- n* L5 p& z6 _, z8 R( [3 [
  41. subplot(2,1,2);plot(x,newh,'r-o',x,glhyl,'b--+');
    8 u; A- W. p* p. O9 u
  42. legend('网络输出货运量','实际货运量');
    9 Z8 j- q- `& ]6 n3 u
  43. xlabel('年份');ylabel('货运量、万吨');
    : L6 G' y, h( h8 T0 m  F
  44. title('运用工具箱货运量学习和测试对比图');
    1 u8 I7 ~1 Y  ~! b. X. b
  45. ) W% F1 Q/ ~( a- n' ]
  46. %新数据仿真4 M; Z& t: a5 `# u
  47. pnew=[73.39,75.555 }0 C# P( l- M6 |4 }
  48.      3.9635,4.0975
    + I6 h) {0 S, C+ u4 \, |; x7 t
  49.      0.9880,1.0268];
    ; t( V& A& I  m  I6 Z
  50. pnewn=mapminmax('apply',pnew,ps1);- u1 c- z; ?8 W1 _
  51. anewn=sim(net,pnewn);
    ( c, k" o; Z$ T+ [
  52. anew=mapminmax('reverse',anewn,ps2)
复制代码
作者: 且生    时间: 2014-7-21 18:22
忽略我上面那个，改动的地方在18，21，25行……求批
  1. clc/ @1 J9 |$ Y7 _
  2. sqrs=[20.55,22.44,25.73,27.13,29.45,30.1,30.96,34.06,36.42,38.09,39.13,39.99,...! @8 K; k6 M8 L5 Q* X/ K% e
  3.     41.93,44.59,47.30,52.89,55.73,56.76,59.17,60.63];5 |. j, M# A- |: Q8 C6 t- e
  4. sqjdcs=[0.6,0.75,0.85,0.90,1.05,1.35,1.45,1.60,1.70,1.85,2.15,2.20,2.25,2.35,...
    6 o& o0 A* e7 w1 n* y1 ]
  5.     2.5,2.6,2.7,2.85,2.95,3.10];
    1 `. F+ [2 w0 b; q3 `
  6. sqglmj=[0.09,0.11,0.11,0.14,0.20,0.23,0.23,0.32,0.32,0.34,0.36,0.36,0.38,0.49,...
    : ]% J1 f2 I: b8 ?' Q4 E4 q- @  @
  7.     0.56,0.59,0.59,0.67,0.69,0.79];/ u9 K6 ^# ~& o) B
  8. glkyl=[5126,6217,7730,9145,10460,11387,12353,15750,18304,19836,21024,19490,20433,..., c) E; a/ y' H. I7 T
  9.      22598,25107,33442,36836,40548,42927,43462];
    ( c. T- c1 ]; o/ `( k# n
  10. glhyl=[1237,1379,1385,1399,1663,1714,1834,4322,8132,8936,11099,11203,10524,11115,...
    , ]- ?' s& L  V) p8 [
  11.      13320,16762,18673,20724,20803,21804];
    2 |# P- Z! g* r* z8 ^
  12. p=[sqrs;sqjdcs;sqglmj];
    ' e9 [. l4 z4 E% p
  13. t=[glkyl;glhyl];
    1 Y. t- ?4 ]: }* ?: p$ k+ L
  14. %数据归一化! H: B  k9 g" N  i* ]" r4 S
  15. [pn,ps1]=mapminmax(p);
    1 b1 f% a$ D$ n
  16. [tn,ps2]=mapminmax(t);- O" I& m4 \( ~. [
  17. %dx=[-1,1;-1,1;-1,1];
    # w0 l2 j! s" W. e
  18. p0=minmax(pn);t0=minmax(tn);
    " E. I1 E/ I8 g+ r
  19. # k9 C# J; _+ p8 K6 a' G
  20. %BP网络训练) m2 `  h6 |, E  |1 ]
  21. net=newff(p0,t0,[3,7,2],{'tansig','tansig','purelin'},'traingdx');
    : E* P, H( ]; s4 N
  22. net.trainParam.show=1000;
    / P/ K1 K; |) t% x) q% p
  23. net.trainParam.Lr=0.05;
    3 ~# e  ^4 Z$ I2 _" P$ V; s& v
  24. net.trainParam.epochs=50000;
    1 R+ V: _1 I' [% {% G& x
  25. net.trainParam.goal=0.65*10^(-5);
    8 T* V2 N4 B& R4 F7 A/ x% V
  26. net=train(net,pn,tn);
    2 o2 a& j* P4 Z7 g+ T

  27. , P* }: T* Y8 G& f6 T+ ?3 G
  28. %利用原数据对BP网络仿真
    ; a/ `  c$ K/ Q0 O  t
  29. an=sim(net,pn);; n  J2 j' n2 x) R3 o* f- t
  30. a=mapminmax('reverse',an,ps2);  e5 i: H/ y) ]9 _
  31. ; X3 l1 k; Q3 v* Z. p, A$ `" h
  32. %仿真结果与原数据对比测试 6 a, V) U- v+ J" P8 c5 G' v3 U- K
  33. x=1990:2009;
    ; C9 Y: T$ ?/ w
  34. newk=a(1,:);
    ( i8 x  y5 U  c7 M
  35. newh=a(2,:);
    - i, y1 ]; ^, h6 _8 g. J9 t
  36. figure(2);
    3 X4 S- B* @: ?- E
  37. subplot(2,1,1);plot(x,newk,'r-o',x,glkyl,'b--+');8 j8 z- G8 _. g0 }3 X" E
  38. legend('网络输出客运量','实际客运量');2 a, j& q& \" n1 R4 c7 t$ R0 h& H
  39. xlabel('年份');ylabel('货运量、万人');% L7 F: F; l: E; D' D
  40. title('运用工具箱客运量学习和测试对比图');$ D. Y4 b6 J3 T( E! }
  41. subplot(2,1,2);plot(x,newh,'r-o',x,glhyl,'b--+');
    3 `9 p  W% }2 F0 y5 t
  42. legend('网络输出货运量','实际货运量');
    1 `( ]9 d# Y/ I3 s7 W. S5 I7 S. L! P
  43. xlabel('年份');ylabel('货运量、万吨');
    9 x- F+ ]6 `" r" H
  44. title('运用工具箱货运量学习和测试对比图');
    2 O% F& p$ ~' s
  45. 1 r* W/ d' s2 S  Z1 K  b
  46. %新数据仿真
    ; h3 D  X6 H/ d5 }' V
  47. pnew=[73.39,75.55
    3 @7 q' O+ p) v8 M
  48.      3.9635,4.0975+ p/ c8 J( B/ f( a* K' _
  49.      0.9880,1.0268];2 l( N. ?; n7 P( `  {8 I( n
  50. pnewn=mapminmax('apply',pnew,ps1);
    + b' l6 |+ k  M, u% W
  51. anewn=sim(net,pnewn);
    / K# w" |6 s9 n+ k2 ]1 R
  52. anew=mapminmax('reverse',anewn,ps2)
复制代码
作者: T-Eric    时间: 2014-7-22 21:14
且生 发表于 2014-7-21 18:22 * P% a+ F* z0 D* O
忽略我上面那个，改动的地方在18，21，25行……求批
% Z3 H$ d+ p- M6 X8 J
确实改善了很多，很是感谢。但效果还是不太理想，而且为何只学习了几十次就停了呢？即使我修改了目标精度。

p1.jpg (166.22 KB, 下载次数: 540)

p1.jpg

p2.jpg (158.1 KB, 下载次数: 499)

p2.jpg

作者: 且生    时间: 2014-7-22 23:35
  1. %BP网络训练
    4 {/ a. n6 x9 }/ j! o/ @
  2. net=newff(p0,t0,6,{'tansig'},'traingd');
    1 E, U$ [2 j4 U1 \
  3. net.trainParam.show=1000;6 E2 b$ S: S& l. W! e
  4. net.trainParam.Lr=0.05;" p9 B* V3 |& J- r
  5. net.trainParam.epochs=2000;5 I7 }2 S! X0 L# f/ I' }8 s
  6. net.trainParam.goal=0.65*10^(-4);* o- h. w7 T5 M
  7. net=train(net,pn,tn);
复制代码
我只改了这里面的，  y! [$ b8 E5 p: U
一、改成单隐含层的，6个节点/ @! A+ ~: }. j& n
二、训练函数改成梯度下降BP算法 traingd( X; |" H0 J& }* K- G" I. v
三、迭代次数改成2000
) e' N6 M' F% D' ]上面的参数是自己试的，我也不知道为什么。; L, E& k3 S' O" @' E( x/ \
由于这玩意儿比较不靠谱，楼主多运行几次就能找到拟合的比较好的网络。
4 p3 O1 }# K. D# i) O关键问题是有没有过拟合我也不知道，等大神来解答吧
作者: 且生    时间: 2014-7-22 23:36
因为样本比较少，所以训练函数没有选会调节学习率的
作者: 狼之魂汪洋    时间: 2014-8-6 14:00
你这例题是在什么书上找的？
作者: T-Eric    时间: 2014-8-7 20:55
狼之魂汪洋 发表于 2014-8-6 14:00
7 w4 z" L0 {% }- Q, F3 o你这例题是在什么书上找的？

" j0 u0 I1 R6 _# z  x/ O就是那本《matalb在数学建模中的应用》



欢迎光临 数学建模社区-数学中国 (http://www.madio.net/) Powered by Discuz! X2.5