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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！！
$ q  @2 E& d  T% H6 |6 u5 w2 o0 D% r& p) M+ Y3 Y3 k3 H
%原始数据输入
8 D' n$ E- v% K+ f: B6 V; fclc
1 \5 B& n: P9 V3 O5 i" u$ l7 e- gsqrs=[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 i7 [' U6 h& z$ w0 ]    41.93,44.59,47.30,52.89,55.73,56.76,59.17,60.63];
- ~3 h# l, n1 M( }" nsqjdcs=[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,...
3 M" G- f. }7 o1 C4 {6 b/ O    2.5,2.6,2.7,2.85,2.95,3.10];& k+ K: W& P/ x6 D/ X9 t
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,...7 S3 @( ^4 d: I0 H
    0.56,0.59,0.59,0.67,0.69,0.79];
* d4 w0 R* O6 r2 rglkyl=[5126,6217,7730,9145,10460,11387,12353,15750,18304,19836,21024,19490,20433,...- k% Z) v6 A  J* |( {9 k. T/ e  Z
    22598,25107,33442,36836,40548,42927,43462];
9 _) {! E7 L0 [# c  Q/ uglhyl=[1237,1379,1385,1399,1663,1714,1834,4322,8132,8936,11099,11203,10524,11115,...  s+ S2 h# @. e* i7 o4 q) @
    13320,16762,18673,20724,20803,21804];
5 b1 [* L7 _% @6 r& c, o3 tp=[sqrs;sqjdcs;sqglmj];0 b9 N& k$ R1 P0 a' y
t=[glkyl;glhyl];
0 H9 C' f! n7 Q3 i9 e/ d* g: W: X. a+ D* x2 {, q9 }* |
%数据归一化
+ p; `. M* D+ l( V8 f$ p+ x[pn,ps1]=mapminmax(p);
9 G; M  P: r2 `  e" X" v[tn,ps2]=mapminmax(t);) S1 ~) l3 J3 j3 `# Q, v
dx=[-1,1;-1,1;-1,1];# z9 x1 v3 b0 K$ s$ c7 Z- o

$ N4 e+ i1 f- J9 w7 i3 y! y%BP网络训练
$ r* u7 @1 \. {3 T" Enet=newff(p,t,[3,7,2],{'tansig','tansig','purelin'},'traingdx');8 N! j! g1 W7 Z' ^* d% s9 u
net.trainParam.show=1000;1 K; C/ s7 k6 U& M, e& [; J
net.trainParam.Lr=0.05;
3 E2 _4 j5 [# ^; n+ ]+ c# anet.trainParam.epochs=50000;
8 O9 M; |' T& N2 ~* b! a! gnet.trainParam.goal=0.65*10^(-3);
. N9 m  `" L- f) C& q3 e9 |net=train(net,pn,tn);% o2 x) M  Q: \* M; B6 \3 f

% V, |7 N8 i! Y: h1 g- R%利用原数据对BP网络仿真# H8 D; j) v" N! O  v6 C) |
an=sim(net,pn);
# l$ b& j6 Q6 v/ ?a=mapminmax('reverse',an,ps2);& w; _3 X1 E7 D" k0 n: y% K- Y
* `4 {( s+ W3 i/ r: U
%仿真结果与原数据对比测试
- y9 T" Q2 u3 R9 N* hx=1990:2009;( g& u  b6 H0 n
newk=a(1,:);
# |) ]6 ?# k% o* w: n. S$ Wnewh=a(2,:);
4 w+ w5 Z, k( a. g; G5 Gfigure(2);! y5 R) n% n( _5 W/ g7 h6 }  k# O
subplot(2,1,1);plot(x,newk,'r-o',x,glkyl,'b--+');
( k' f8 h( b( d& Flegend('网络输出客运量','实际客运量');# h7 Q+ E( z5 z$ o% ^
xlabel('年份');ylabel('货运量、万人');
2 R4 e  d  h, N3 M; V9 y. w# P4 dtitle('运用工具箱客运量学习和测试对比图');
. H" S( ?/ r6 c6 Z, Ysubplot(2,1,2);plot(x,newh,'r-o',x,glhyl,'b--+');
& G9 s$ }- r% mlegend('网络输出货运量','实际货运量');9 G3 ]( a( ]+ U
xlabel('年份');ylabel('货运量、万吨');$ z6 V" O+ @+ q. O
title('运用工具箱货运量学习和测试对比图');
6 v* |4 j5 K1 u
  T- L! [: F) l9 \3 \" E8 R%新数据仿真0 C6 o5 E* s" E3 H7 Z$ t
pnew=[73.39,75.553 w8 U$ ~1 P! @) f2 k: g1 z* `
    3.9635,4.0975
/ l$ x9 x; @% W, ]2 x2 I  x% R# @    0.9880,1.0268];8 U2 j3 ]0 s8 y7 i/ c) g; M
pnewn=mapminmax('apply',pnew,ps1);5 \" b9 D. C( H
anewn=sim(net,pnewn);
$ ^% O* g/ k" a' t) O  L0 @- c% Zanew=mapminmax('reverse',anewn,ps2)
/ k8 o; M# f; k: ?- u# h1 h' B- U" N! W+ U& X

`VCWMZD9E$D~NHRR~AT9B4D.jpg (120.2 KB, 下载次数: 502)

`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
% L# v6 {, }& I( X( f8 s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 ...

0 i2 q. @4 Q/ k8 }$ _  t6 r因为版本更新，Matlab中的Newff命令用法有所改变，原命令为：9 |2 C7 ~; W  W
net=newff(dx,[3,7,2]{'tansig','tansig','purelin'},'traingdx');
$ V& R9 m& R7 e. J我修改为：
- G* H$ i+ x+ ^net=newff(p,t,[3,7,2],{'tansig','tansig','purelin'},'traingdx');+ N  S8 X) [; Y  P- U$ q
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：! O7 j% d' J9 ^7 g
[pn,minp,maxp,tn,mint,maxt]=premnmx(p,t);
4 j  N: {) g; P. Q- J4 Ua=postmnmx(an,mint,maxt);
$ @; F. I; K" \6 x8 X  Q  k8 \5 Dpnewn=tramnmx(pnew,minp,maxp);
3 l( Q7 z! J; r+ `' xanew=postmnmx(anewn,mint,maxt)3 B7 y: a' k: r1 {2 P- L" b1 ^
我修改为：
$ v2 C% z  B0 P[pn,ps1]=mapminmax(p);[tn,ps2]=mapminmax(t);! Y) @3 C( X* g1 e: c2 w# t4 {
a=mapminmax('reverse',an,ps2);8 n8 c4 C1 p- r1 N
pnewn=mapminmax('apply',pnew,ps1);* o/ ^6 t' M- c& i
anew=mapminmax('reverse',anewn,ps2)+ K7 l  f4 }' L7 {( B: |* I3 A! v

4 U& |7 w7 _7 s1 X8 O; S! |& D原程序为：9 x, F1 y0 z( J  g
%原始数据输入, U5 C) Z/ ^1 S% i* e
clc
  M8 \8 e% R, e6 G- f7 Xsqrs=[20.55,22.44,25.73,27.13,29.45,30.1,30.96,34.06,36.42,38.09,39.13,39.99,...
* a& M; |4 s% m1 w) U    41.93,44.59,47.30,52.89,55.73,56.76,59.17,60.63];
+ n# Q  F4 s" r* O' M* Gsqjdcs=[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 b6 Q3 N/ m* \8 M    2.5,2.6,2.7,2.85,2.95,3.10];
% j: F1 v) U; g8 R- tsqglmj=[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,...
& z* k4 Y  u/ R  p( ^0 ~    0.56,0.59,0.59,0.67,0.69,0.79];
- z3 w) w. i. Z. U( hglkyl=[5126,6217,7730,9145,10460,11387,12353,15750,18304,19836,21024,19490,20433,...0 G$ T& ^3 `) ?+ V& r
    22598,25107,33442,36836,40548,42927,43462];8 F7 N4 F/ f$ @
glhyl=[1237,1379,1385,1399,1663,1714,1834,4322,8132,8936,11099,11203,10524,11115,...8 c1 w8 l- a5 f! H( a& y
    13320,16762,18673,20724,20803,21804];
7 ?  r9 O& m/ v7 [- ?# \5 @p=[sqrs;sqjdcs;sqglmj];) K' ]3 U# s: o( |( ^9 G
t=[glkyl;glhyl];. g% \6 y3 I4 n1 @0 ], a  e
( s4 }& n, ^( x3 |+ u: G; B& j
%数据归一化
: `3 \7 P7 V5 ~# `, ][pn,minp,maxp,tn,mint,maxt]=premnmx(p,t);: o( }5 i7 [+ }* L' p; c# x
dx=[-1,1;-1,1;-1,1];
* i1 ?$ o$ ]4 ~' t# f, I3 P& M
1 W; @3 Q$ e/ z6 R- ^  O%BP网络训练
; O9 B$ d( U" m, M8 Ynet=newff(dx,[3,7,2],{'tansig','tansig','purelin'},'traingdx');" i! ?# n: D/ _6 [
net.trainParam.show=1000;
6 S  d7 ]' @6 T! m$ `1 s6 g9 _net.trainParam.Lr=0.05;
6 a' S" ~8 t# g, F- i& k& v6 E; Cnet.trainParam.epochs=50000;
- X- d* [( s+ {# _6 q  Unet.trainParam.goal=0.65*10^(-3);1 y- ?' {9 D. K$ j* ?& h3 v' ?( _3 ]
net=train(net,pn,tn);
5 G/ I8 z% M7 V5 V
2 }4 H% s  L9 M; ?%利用原数据对BP网络仿真1 ]9 ~8 d3 U$ i
an=sim(net,pn);
' }$ ~( j( G3 ]$ W4 a& Va=postmnmx(an,mint,maxt);
! W& ]( B: ?. U  P6 f' y& t- b* |6 [5 ^9 H* Q3 b# X: d! v
%仿真结果与原数据对比测试5 R8 |! h0 \2 N' Z  U
x=1990:2009;
3 |5 |* q; y" J& ^$ |: z/ knewk=a(1,;2 d/ |, U$ |2 Z
newh=a(2,;
% ?# n# @  G  N- `. O# s. w, qfigure(2);
; M) J0 b* y" h1 g6 Ksubplot(2,1,1);plot(x,newk,'r-o',x,glkyl,'b--+');
/ V' ^; S; d2 }legend('网络输出客运量','实际客运量');, z+ d9 o* \- N# O5 r
xlabel('年份');ylabel('货运量、万人');
2 G, _2 Z' U- Y$ m" ?9 F8 Y( ptitle('运用工具箱客运量学习和测试对比图');
3 X) A) L7 D! P+ B! y3 Nsubplot(2,1,2);plot(x,newh,'r-o',x,glhyl,'b--+');
0 i: [7 \8 c! A* s9 x+ llegend('网络输出货运量','实际货运量');, u6 f% ^. W! e9 P2 H- E) J  y
xlabel('年份');ylabel('货运量、万吨');
, U+ m! ?, E+ F2 t- mtitle('运用工具箱货运量学习和测试对比图');
* Y/ j0 d5 m- v  n) m$ M
# f" W5 Z3 H/ e+ r3 B%新数据仿真
2 W0 H- d9 E* T1 opnew=[73.39,75.555 n9 p6 y- k" W( W' T; K+ t
    3.9635,4.0975
7 A+ Z0 o/ S3 h9 v% r* y/ Y9 L    0.9880,1.0268];/ L5 P' d# M8 [1 a/ O! W
pnewn=tramnmx(pnew,minp,maxp);
" ]. M  u8 I1 v6 T3 banewn=sim(net,pnewn);
) c, `3 W5 V- n* }+ d8 X/ g6 ^, [/ ~anew=postmnmx(anewn,mint,maxt). s% M3 C& ^5 z# l( ?
5 u( N( V9 r- O" c
修改后程序为：
- c5 A$ Y6 H4 e6 Q* y" }6 V; |%原始数据输入/ q+ E& j% F0 [) w( m& A6 W
clc
. X& I' G$ ~6 e. n- o% p) Nsqrs=[20.55,22.44,25.73,27.13,29.45,30.1,30.96,34.06,36.42,38.09,39.13,39.99,...
3 D% U0 T+ K' o% K# z  r    41.93,44.59,47.30,52.89,55.73,56.76,59.17,60.63];
) A& s: l! O  B8 O  n. rsqjdcs=[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,...
& Z4 g: @" e- ~. Y4 P1 x    2.5,2.6,2.7,2.85,2.95,3.10];
- w, r1 M3 O0 _4 c( zsqglmj=[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,...  L- l2 X0 M9 S) c: i6 V" h
    0.56,0.59,0.59,0.67,0.69,0.79];7 p' `! s: B- t
glkyl=[5126,6217,7730,9145,10460,11387,12353,15750,18304,19836,21024,19490,20433,...
5 b$ q7 ]3 L# y3 W    22598,25107,33442,36836,40548,42927,43462];
  v' J9 W& P- a# _$ Lglhyl=[1237,1379,1385,1399,1663,1714,1834,4322,8132,8936,11099,11203,10524,11115,...4 K+ A0 R  u- r+ O( |. c1 C( @* X' j
    13320,16762,18673,20724,20803,21804];
4 }: @) z. A# Sp=[sqrs;sqjdcs;sqglmj];9 N& B6 E! ?, I% R: V" D
t=[glkyl;glhyl];2 k- H1 P( M! d; ^
, X9 E6 y  b7 d. S* H5 V+ w
%数据归一化
( D: C' N8 B  i% d[pn,ps1]=mapminmax(p);
* j5 B4 `6 d* k9 {. K* B[tn,ps2]=mapminmax(t);. N& e. P1 q  f9 p4 A# x% G
: m& p, G* i) c* k: M' _7 Z
%BP网络训练3 d$ Z2 J/ K/ b* a4 n
net=newff(p,t,[3,7,2],{'tansig','tansig','purelin'},'traingdx');
3 e; ]8 C' v% R0 }+ wnet.trainParam.show=1000;2 m1 ^" i1 U) m8 }4 N2 a2 `
net.trainParam.Lr=0.05;
9 ^, b5 A- |. Z) i0 }net.trainParam.epochs=50000;
( b- E# E" o5 U; H" K* Rnet.trainParam.goal=0.65*10^(-3);
) v: s( e+ ^: l$ C1 p* Inet=train(net,pn,tn);7 \- E9 \5 L2 s# y
- c; ~, E& e9 N5 d0 p$ f) n
%利用原数据对BP网络仿真* N: j! f3 Y8 {$ |4 O* x5 P9 k5 K
an=sim(net,pn);$ C& a: _# ?7 D0 U! s5 o* Q
a=mapminmax('reverse',an,ps2);/ U* }$ Y6 g: T( [
, ]' c1 G2 S0 z; y0 W/ \* ^0 |. S
%仿真结果与原数据对比测试# R/ y1 h/ M* a6 @6 z. g4 t3 G8 \
x=1990:2009;2 D2 e. p, o: L) R$ ~
newk=a(1,;" a8 f+ ]3 N4 g$ h! W! r
newh=a(2,;$ r2 F, b/ A5 O2 Z
figure(2);* `) ]( d5 \! b) u0 J! D$ y
subplot(2,1,1);plot(x,newk,'r-o',x,glkyl,'b--+');9 t# L% E3 u5 S
legend('网络输出客运量','实际客运量');
% @* u$ M: d: D! z! D* qxlabel('年份');ylabel('货运量、万人');
6 H6 p$ I7 H: F4 L* C/ mtitle('运用工具箱客运量学习和测试对比图');
  P. e  v) a. R7 J5 C" F  qsubplot(2,1,2);plot(x,newh,'r-o',x,glhyl,'b--+');: |( a3 S! l4 x8 r+ `
legend('网络输出货运量','实际货运量');, o# \  H0 e# ^- x& d
xlabel('年份');ylabel('货运量、万吨');
) t2 v. ^- @1 k% X" O1 Q. Utitle('运用工具箱货运量学习和测试对比图');
5 H) S/ H2 J$ s9 n  ^1 d0 ^3 S% Q' m& u# w
%新数据仿真& \$ f. h$ d/ S) V- {* ?
pnew=[73.39,75.55
. V8 ?+ M; f% {/ l7 j6 S    3.9635,4.0975# n- c* S' k# o( l! N
    0.9880,1.0268];. |$ g! A' a% ?5 U8 C
pnewn=mapminmax('apply',pnew,ps1);
% v+ i: g1 L3 Y0 \: H. ^* S' Janewn=sim(net,pnewn);
# }9 ~! s9 d7 C. Y; sanew=mapminmax('reverse',anewn,ps2)/ L3 ?# w4 D6 N: d$ p# C/ }
（修改的地方用颜色标记了）7 t, F2 c) ~) ~% @3 C: X
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
    # }* f# x4 k8 `0 i+ ]1 \
  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,...
    4 L5 R1 h2 V8 E: Z9 c/ Q. S5 {
  3.     41.93,44.59,47.30,52.89,55.73,56.76,59.17,60.63];
    ! ~! z# F3 e+ ]; x) m
  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,...  G" p- v2 K* L( d. r; X
  5.     2.5,2.6,2.7,2.85,2.95,3.10];: J* _# N. Y( H  P, u
  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,...  @9 S* \# d8 S
  7.     0.56,0.59,0.59,0.67,0.69,0.79];
    2 N! p/ ]( k9 z1 I+ U* Y6 P
  8. glkyl=[5126,6217,7730,9145,10460,11387,12353,15750,18304,19836,21024,19490,20433,...4 Z2 r3 E9 y2 r. [$ L
  9.      22598,25107,33442,36836,40548,42927,43462];
    & |& k+ V2 @& [
  10. glhyl=[1237,1379,1385,1399,1663,1714,1834,4322,8132,8936,11099,11203,10524,11115,...
    1 }1 n* K3 _3 t
  11.      13320,16762,18673,20724,20803,21804];
    ! b) z7 B0 d( K+ n9 O/ C
  12. p=[sqrs;sqjdcs;sqglmj];+ M$ X" c1 t" J7 M/ k
  13. t=[glkyl;glhyl];
    . x5 i2 c- }' i* N% B2 o2 m
  14. %数据归一化  _& ?( M& ~8 q5 E( R4 E3 H
  15. [pn,ps1]=mapminmax(p);& D4 g: G5 S6 W9 T7 x& i' \  x7 p& Y
  16. [tn,ps2]=mapminmax(t);! \+ t+ V3 ]. w+ Y- T% @
  17. %dx=[-1,1;-1,1;-1,1];( k/ D/ _, i' @/ Z. j: N- N
  18. [color=Red] p0=minmax(pn);t0=minmax(tn);[/color]
    % R% j$ H6 ?& s0 A0 Q9 p9 k4 U
  19. 6 A1 v, ^- e* ]; p  V
  20. %BP网络训练$ Y0 h0 G( U6 h" h! i7 [* ^! q8 Z
  21. [color=Red] net=newff(p0,t0,[3,7,2],{'tansig','tansig','purelin'},'traingdx'); [/color]
    & }0 {' C- p2 C4 K$ C
  22. net.trainParam.show=1000;
    % c# F4 b- U/ I
  23. net.trainParam.Lr=0.05;
    9 [7 b6 c$ _! p4 a
  24. net.trainParam.epochs=50000;$ A( U4 F3 f  m$ E1 X/ M/ C
  25. [color=Red] net.trainParam.goal=0.65*10^(-5);[/color]: C, D+ Q* E3 h- A
  26. net=train(net,pn,tn);
    9 W, h8 |+ E! i6 b: B
  27. : w3 J5 ~8 r# W1 z" g6 b+ b" p
  28. %利用原数据对BP网络仿真
    + j0 m) B1 z+ k! W/ }
  29. an=sim(net,pn);0 O& k% ]* p) b: S( g+ P$ J, ~
  30. a=mapminmax('reverse',an,ps2);
    # e& I6 B$ `1 c" v* B8 k. w7 q

  31. , [; R. d1 M1 `, {" y/ ~
  32. %仿真结果与原数据对比测试
    ) m" v. E+ H7 V( y* B& T
  33. x=1990:2009;4 d3 d( c* q; t6 x0 _! ~* Z5 y
  34. newk=a(1,:);
    8 o& V/ C0 ~0 p! g) f" Z: b& C
  35. newh=a(2,:);! X% K* D8 z- m2 J3 \
  36. figure(2);8 T: A) B3 I9 v$ X
  37. subplot(2,1,1);plot(x,newk,'r-o',x,glkyl,'b--+');/ v6 E8 F  ^3 Z5 _, v6 t# K( x
  38. legend('网络输出客运量','实际客运量');3 v7 r- D! x5 T
  39. xlabel('年份');ylabel('货运量、万人');
    # p; N: H# o  ^( K: C
  40. title('运用工具箱客运量学习和测试对比图');  e$ F( p; Q. D. _# U) f! p0 R
  41. subplot(2,1,2);plot(x,newh,'r-o',x,glhyl,'b--+');% t( y2 e. z' t- n
  42. legend('网络输出货运量','实际货运量');
    2 F1 X/ W, S7 G8 Y" H7 v2 ]
  43. xlabel('年份');ylabel('货运量、万吨');
    7 I7 X1 f# x4 W2 f; M% N* L( n
  44. title('运用工具箱货运量学习和测试对比图');
    ) {2 k) f& k+ r" v
  45. 1 e- p6 a' U6 i/ `
  46. %新数据仿真
    ' B: G" i. K/ M" V: A
  47. pnew=[73.39,75.550 k5 [, F* a3 e
  48.      3.9635,4.0975. D& r0 {5 u4 a2 n; w% g
  49.      0.9880,1.0268];% g& \' F/ R/ \3 G
  50. pnewn=mapminmax('apply',pnew,ps1);
    0 i' H: H; `, D& d2 n7 Q
  51. anewn=sim(net,pnewn);# i- _' B  f. `: x- S
  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
    # |; h& F" G0 C8 k
  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,...4 B0 n1 H5 d8 _: \2 c
  3.     41.93,44.59,47.30,52.89,55.73,56.76,59.17,60.63];1 b% T& R& Z. |* K8 Y; Y
  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,...
    " X4 S' {% k6 K% H" {" K9 {7 s; `
  5.     2.5,2.6,2.7,2.85,2.95,3.10];
    % K. z- `  y* n7 ]5 t
  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,...
      @$ E/ S( L1 B
  7.     0.56,0.59,0.59,0.67,0.69,0.79];0 f, \1 b# I& u: |
  8. glkyl=[5126,6217,7730,9145,10460,11387,12353,15750,18304,19836,21024,19490,20433,...
    8 M1 t: K* n) @, x
  9.      22598,25107,33442,36836,40548,42927,43462];9 H8 S* ]1 [$ u: k
  10. glhyl=[1237,1379,1385,1399,1663,1714,1834,4322,8132,8936,11099,11203,10524,11115,...: u( D% I! G+ m1 B  Z
  11.      13320,16762,18673,20724,20803,21804];4 q4 s( j, I3 c" s
  12. p=[sqrs;sqjdcs;sqglmj];  \: o9 w* H. s1 v
  13. t=[glkyl;glhyl];
    # e) }: ^6 q& q6 F1 f$ j1 z+ v2 n
  14. %数据归一化3 N4 \8 Z  G5 `8 A' O( W2 b0 W
  15. [pn,ps1]=mapminmax(p);
    ; Y9 x5 v. L2 ?
  16. [tn,ps2]=mapminmax(t);
    " a3 ?* `5 w) R/ t3 a- K* @
  17. %dx=[-1,1;-1,1;-1,1];: e# @# e& `3 O( N5 l
  18. p0=minmax(pn);t0=minmax(tn);
    , A+ C' F# n6 y! H4 K: x6 d

  19. & m/ t3 f4 Y) g) t1 g' C
  20. %BP网络训练
    * d& v/ }# {9 Z
  21. net=newff(p0,t0,[3,7,2],{'tansig','tansig','purelin'},'traingdx');
    / l4 c% `2 A" x) a" W. X# C, v
  22. net.trainParam.show=1000;
    " \% L" j; v  v+ n) E; S
  23. net.trainParam.Lr=0.05;
    / L3 N5 V7 W6 n' n4 L: j
  24. net.trainParam.epochs=50000;
    . j! a3 U  t2 C& V7 H, v3 ?+ y
  25. net.trainParam.goal=0.65*10^(-5);  p! t( q5 |, O; @; r% Z) C1 f- u9 r% p
  26. net=train(net,pn,tn);1 M7 x1 R4 c# u$ a

  27. ' l& J0 d2 S& t' G+ @
  28. %利用原数据对BP网络仿真+ L& B$ y1 O# A. h
  29. an=sim(net,pn);5 f6 N& m$ h1 R/ G6 Z
  30. a=mapminmax('reverse',an,ps2);
    2 e2 Z3 N( w( [4 l* e4 {+ w7 o4 Y
  31.   X# c! d+ I3 Z* T, E5 L; y
  32. %仿真结果与原数据对比测试
      x, `& ^4 C, }1 k( H; z* k" k5 ~
  33. x=1990:2009;
    , B% t  s. o3 O7 q9 `1 R$ U, g( o! G" f
  34. newk=a(1,:);
    $ F6 D+ ?1 N( D' y/ P& `& E
  35. newh=a(2,:);
    0 o1 Z" \( w; b7 E" {
  36. figure(2);" U- z' ]& u$ @: ?% P) D8 H8 b) ^
  37. subplot(2,1,1);plot(x,newk,'r-o',x,glkyl,'b--+');. ^! N1 \1 ^7 Q& @+ J. Q, q
  38. legend('网络输出客运量','实际客运量');1 ]' A' q( e2 T7 p# \4 ~
  39. xlabel('年份');ylabel('货运量、万人');/ x0 M% G( F; v3 f# |  y1 W0 l
  40. title('运用工具箱客运量学习和测试对比图');
    # S$ E' {# ~  ~- T: ^
  41. subplot(2,1,2);plot(x,newh,'r-o',x,glhyl,'b--+');& t/ I. r8 s0 _+ C% n
  42. legend('网络输出货运量','实际货运量');
    # m8 v. d& W# _' J' r2 S1 W
  43. xlabel('年份');ylabel('货运量、万吨');
    / {- ~( L( ^( a; q  G
  44. title('运用工具箱货运量学习和测试对比图');
    2 n, _/ C" y4 }: X7 Y% P
  45. " h8 M) f& v5 Z7 D, l
  46. %新数据仿真! d0 i9 F8 m+ g  h9 s; G& U
  47. pnew=[73.39,75.55
    4 |) d4 V- P0 x- j; Q
  48.      3.9635,4.0975- U- e/ I8 f( o& L! L( k4 l5 ~
  49.      0.9880,1.0268];
    ) L8 \4 `3 |3 {0 `* l
  50. pnewn=mapminmax('apply',pnew,ps1);5 j, B! Y; j: X# _- c  @0 g
  51. anewn=sim(net,pnewn);  v4 O, @. P2 l& z1 N* ^2 M  p
  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
6 c- v7 ~+ }! k# q" _忽略我上面那个，改动的地方在18，21，25行……求批
! T0 K( L/ l7 f# U
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。

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p1.jpg

p2.jpg (158.1 KB, 下载次数: 494)

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作者: 且生    时间: 2014-7-22 23:35
  1. %BP网络训练
    6 m' w! Q$ w5 A! W; A1 p5 Q
  2. net=newff(p0,t0,6,{'tansig'},'traingd'); 9 F: R& c7 P' f9 I) A& N; p; J
  3. net.trainParam.show=1000;
    ; J4 {/ u% I" _5 m  V  x5 m
  4. net.trainParam.Lr=0.05;
    & k7 f$ i/ L% q" _
  5. net.trainParam.epochs=2000;
    6 v, z2 M2 l: ~6 t
  6. net.trainParam.goal=0.65*10^(-4);
    6 O3 s! d/ U  \* C
  7. net=train(net,pn,tn);
复制代码
我只改了这里面的，4 a( p% L% _. V, e2 G3 o: F* H
一、改成单隐含层的，6个节点
5 }# T: ^" f$ }3 \: j二、训练函数改成梯度下降BP算法 traingd( q0 M+ N5 i$ |* A! y
三、迭代次数改成2000
0 Z+ |! M0 u' A上面的参数是自己试的，我也不知道为什么。' N. n  T( S3 T1 J
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。! ]  H! v5 h  ]3 d& r
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 5 M3 ~2 U8 X; ]0 |! f- x
你这例题是在什么书上找的？

! V) p0 B) M0 {8 J2 k% [就是那本《matalb在数学建模中的应用》



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