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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！！
9 g0 A5 ?4 |4 C* T6 _2 I) r
" w7 g- D+ l/ r8 n9 j%原始数据输入
- ]& Z8 G8 }6 B" qclc' t( B% T3 Z! S% p7 ~3 d. ^: x7 E
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,...
9 Z; q+ K5 e3 h    41.93,44.59,47.30,52.89,55.73,56.76,59.17,60.63];
. R1 t1 u( r; }! \1 `* Vsqjdcs=[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,...
' F1 d$ x: _* O) ]+ j    2.5,2.6,2.7,2.85,2.95,3.10];- h# y3 ^$ ]+ I' n7 |2 b
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 T: Y) x" e: U, t! y0 n' b
    0.56,0.59,0.59,0.67,0.69,0.79];
& i& N' t/ _% y9 m" k2 t( t4 Kglkyl=[5126,6217,7730,9145,10460,11387,12353,15750,18304,19836,21024,19490,20433,...: K; x, j& {/ ?4 K5 ?9 t- i0 v$ W
    22598,25107,33442,36836,40548,42927,43462];! o* ?! r7 R. X2 D
glhyl=[1237,1379,1385,1399,1663,1714,1834,4322,8132,8936,11099,11203,10524,11115,...* \9 m2 h2 {+ V. J' F
    13320,16762,18673,20724,20803,21804];
; I4 ^. U. N3 Vp=[sqrs;sqjdcs;sqglmj];
2 ]( W# I+ o, j+ F* xt=[glkyl;glhyl];
) R" s- c2 v9 f9 M, F* m4 i- t5 ^* M/ m: k* n0 l$ E
%数据归一化9 u1 ~& ?$ Z4 Y. f3 G' m% n
[pn,ps1]=mapminmax(p);  V7 g1 W. F# D3 o5 j2 g) ^
[tn,ps2]=mapminmax(t);
" q1 ]) ^+ z" |/ w7 m$ W# odx=[-1,1;-1,1;-1,1];3 G0 V, M" b4 b+ [  i) o3 U8 J
0 x) D- F( [5 X% R- Z
%BP网络训练' H' i5 g' f: {
net=newff(p,t,[3,7,2],{'tansig','tansig','purelin'},'traingdx');
# I6 e; a" M7 t( q0 s2 pnet.trainParam.show=1000;6 x7 N6 w1 F# ~+ H5 D  F, X
net.trainParam.Lr=0.05;# H* h/ f( Z; q, m7 b* f) `
net.trainParam.epochs=50000;
5 X; Q% C9 D$ p9 @2 n2 Anet.trainParam.goal=0.65*10^(-3);
% n2 P( L+ h% D* E% w, Knet=train(net,pn,tn);
7 X7 e0 W9 }4 f- x) j5 Q( _% _, J7 A- k2 U+ v
%利用原数据对BP网络仿真
( I, Q( S( v6 m4 h+ ?; Ean=sim(net,pn);0 M2 `( ]+ h6 J+ Y9 P1 V( ?( J5 K
a=mapminmax('reverse',an,ps2);5 E% N' p5 L2 ~; z

' m  o7 N6 {, n2 [5 [%仿真结果与原数据对比测试$ m5 |8 K- h. i: j
x=1990:2009;' X% o, ?; I9 {# g
newk=a(1,:);' \! b7 n# @4 k+ x3 I
newh=a(2,:);
: c' H- q2 r% ifigure(2);
' P6 y8 {9 {, ?5 nsubplot(2,1,1);plot(x,newk,'r-o',x,glkyl,'b--+');
6 @1 k, g; c9 s. y) i9 i/ U% Klegend('网络输出客运量','实际客运量');
- Q  f7 P% {+ c+ }( Lxlabel('年份');ylabel('货运量、万人');
1 ~3 n' ?3 ~- etitle('运用工具箱客运量学习和测试对比图');
+ ?( k  i4 B7 d0 O8 S/ L2 osubplot(2,1,2);plot(x,newh,'r-o',x,glhyl,'b--+');
* B; L3 S: k3 G+ x0 Glegend('网络输出货运量','实际货运量');8 {/ {. n2 w/ H3 d
xlabel('年份');ylabel('货运量、万吨');7 s; y& Z2 Q9 M9 L2 M; \2 ~
title('运用工具箱货运量学习和测试对比图');
5 X0 a4 m/ L& s3 I* h$ J- P- d# V) i) U8 \
%新数据仿真
, @. {8 k0 Y0 _3 {7 ~  ]8 Npnew=[73.39,75.55
& j6 W& d& M3 d% Z    3.9635,4.0975* Z/ f, B$ m/ g7 s( u0 O" d  \$ u
    0.9880,1.0268];
9 }& q, i8 G  D9 l6 u2 L6 g& P3 ipnewn=mapminmax('apply',pnew,ps1);
9 o" t( P- ?( e( i, tanewn=sim(net,pnewn);! O9 s. h! x1 t' T
anew=mapminmax('reverse',anewn,ps2)
6 A) G0 k- h0 \; U# E: p4 ?. U
: g9 Y/ L" l  l2 ]

`VCWMZD9E$D~NHRR~AT9B4D.jpg (120.2 KB, 下载次数: 554)

`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
) }; {' H( N! `5 V* o" [% K: i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 ...
( e' G, g5 {) U2 {& M" _% d
因为版本更新，Matlab中的Newff命令用法有所改变，原命令为：7 `: J$ {  Q2 f% c+ u  j) D* L% z
net=newff(dx,[3,7,2]{'tansig','tansig','purelin'},'traingdx');0 z' }* X# p! E; L! L% I& d
我修改为：7 B$ {" c8 C6 s7 f1 U4 O
net=newff(p,t,[3,7,2],{'tansig','tansig','purelin'},'traingdx');9 n2 T. L' ]) M3 Q4 ~
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：
; i0 d: `+ ]9 ~1 o) o3 U[pn,minp,maxp,tn,mint,maxt]=premnmx(p,t);1 Q' r$ @$ v# Y  c0 e
a=postmnmx(an,mint,maxt);2 l. G7 l& g1 K+ \3 E- C
pnewn=tramnmx(pnew,minp,maxp);
% F' Q3 U$ u; t# q4 kanew=postmnmx(anewn,mint,maxt)
. R3 @/ n" v0 H" R我修改为：* o( l5 a" Y" t( Y9 a. j3 q
[pn,ps1]=mapminmax(p);[tn,ps2]=mapminmax(t);
& c9 U0 R) v0 Z  A" T* Da=mapminmax('reverse',an,ps2);
% D$ |3 u- q9 Rpnewn=mapminmax('apply',pnew,ps1);( s3 `* P& |% F) A
anew=mapminmax('reverse',anewn,ps2)1 D( D% a+ M# Q6 A- ?0 `

2 x& z9 Z. B; K3 f原程序为：, P4 E% A! ~- J( h
%原始数据输入
9 |4 ?4 M5 K/ J' c, K& D9 jclc
+ h9 f  H5 V5 ~' d' c6 l  N4 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,...2 \8 |: P. Y, L# U3 \) f
    41.93,44.59,47.30,52.89,55.73,56.76,59.17,60.63];0 i& A0 ]* y" G! y/ G0 V% h  G( }
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,...
" J. K% [: h" u) N/ ?: ?- A0 P0 x    2.5,2.6,2.7,2.85,2.95,3.10];
5 M) {0 |: N) ^* X* w' ?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,...
1 e' S$ X  n; D    0.56,0.59,0.59,0.67,0.69,0.79];! _5 T2 P3 {/ m" b
glkyl=[5126,6217,7730,9145,10460,11387,12353,15750,18304,19836,21024,19490,20433,...
2 i7 |7 Y, n  t" z7 d    22598,25107,33442,36836,40548,42927,43462];! W8 y& z4 b8 C; ?, f- R$ t. R
glhyl=[1237,1379,1385,1399,1663,1714,1834,4322,8132,8936,11099,11203,10524,11115,...
% W: \/ M! \" f+ w& a    13320,16762,18673,20724,20803,21804];
6 p# P1 G4 ]% K* C) j  ]$ Ap=[sqrs;sqjdcs;sqglmj];7 t& Y# |! o6 f3 I' Q
t=[glkyl;glhyl];9 A% p4 G: X! s) h; A' U

1 i( c0 m4 k2 C: C; u4 U%数据归一化3 h2 h: v. W% S9 [. x" [3 C9 }  z. G
[pn,minp,maxp,tn,mint,maxt]=premnmx(p,t);6 q8 g" d) O2 J* k9 e
dx=[-1,1;-1,1;-1,1];
0 p6 L+ F. G( v5 k) d8 t) s* A; g
%BP网络训练% Z: i, F! J% V& R7 d
net=newff(dx,[3,7,2],{'tansig','tansig','purelin'},'traingdx');% g1 i$ N) ~) L% o0 P
net.trainParam.show=1000;9 F* P3 X& C' x2 I5 E
net.trainParam.Lr=0.05;2 z) o/ |, G6 R5 Y: h: a8 X: a
net.trainParam.epochs=50000;1 @* f* y+ Z( \9 G2 p
net.trainParam.goal=0.65*10^(-3);1 w  e) B+ }* O6 B( l9 a
net=train(net,pn,tn);8 ~7 s1 [. o; j' s
% p  D9 W$ N. B5 c. a
%利用原数据对BP网络仿真
1 E/ J. B% q" d+ [0 i; F9 han=sim(net,pn);
$ @5 s5 ^) @( O5 t8 qa=postmnmx(an,mint,maxt);
1 A, n7 G# P& m. V& ^  w
( N' s) E" c' `1 i- v3 ^%仿真结果与原数据对比测试1 ?9 f( d' }& C% D
x=1990:2009;( U- y2 F$ c2 u  v
newk=a(1,;
4 Z3 T* \$ N" N/ g% anewh=a(2,;* U9 l4 Q0 _- B7 q  A5 l% `- Q
figure(2);7 Y, v7 m7 X4 T3 B
subplot(2,1,1);plot(x,newk,'r-o',x,glkyl,'b--+');
. |' B$ ^: `6 V# A  a! W3 b; ulegend('网络输出客运量','实际客运量');/ r' x- ]) `9 @  A7 N8 H0 ]( o
xlabel('年份');ylabel('货运量、万人');
6 W, U. [4 |8 p1 X  Q5 A4 Utitle('运用工具箱客运量学习和测试对比图');
  `, E+ p1 }, Esubplot(2,1,2);plot(x,newh,'r-o',x,glhyl,'b--+');
- d  H* w7 q" ^/ k6 \% m3 T* Z' Zlegend('网络输出货运量','实际货运量');
4 K/ I& c0 s% E, W/ E8 y+ wxlabel('年份');ylabel('货运量、万吨');
. z7 v$ T/ D% p9 {title('运用工具箱货运量学习和测试对比图');: x4 ?5 l) H3 [  l/ c
& E7 P! D; H; M6 C* [
%新数据仿真9 R' P& x$ X6 u/ |) S4 m
pnew=[73.39,75.55$ h& ]4 \* D. X# Y$ Z1 {+ j" j
    3.9635,4.09754 K6 Q& T' g0 Y) |5 N5 W& W
    0.9880,1.0268];- f( J( Z7 K- E9 v
pnewn=tramnmx(pnew,minp,maxp);2 s8 b( N/ c9 V7 t) T5 g. S; |
anewn=sim(net,pnewn);
. P# [- a# {3 @3 t+ P9 S! Danew=postmnmx(anewn,mint,maxt)8 A: i9 a4 B1 o# [$ W! V
# q/ N8 F5 X% x  T9 w# T0 l
修改后程序为：
* W, C) X/ l4 ?1 I- f* W" A%原始数据输入
  p- i- x0 j" D9 ?& Z& `clc
/ C' S: N, _: Q8 _. N& A- g* Psqrs=[20.55,22.44,25.73,27.13,29.45,30.1,30.96,34.06,36.42,38.09,39.13,39.99,...* P4 u) o% l# z: q9 H4 K
    41.93,44.59,47.30,52.89,55.73,56.76,59.17,60.63];
# w& Z. k4 |( N9 Q7 {0 S, vsqjdcs=[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,...1 u1 g) u  T# U% |" M! h
    2.5,2.6,2.7,2.85,2.95,3.10];
' W% H8 l2 [2 Q: Xsqglmj=[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,...
5 Q! k2 W+ N, q, v3 C    0.56,0.59,0.59,0.67,0.69,0.79];# V8 H/ e# e3 q+ C/ d5 I
glkyl=[5126,6217,7730,9145,10460,11387,12353,15750,18304,19836,21024,19490,20433,...
$ Q: h% q5 F9 z8 w4 c1 s    22598,25107,33442,36836,40548,42927,43462];  \. a6 H1 [$ y1 p. ?! T) v
glhyl=[1237,1379,1385,1399,1663,1714,1834,4322,8132,8936,11099,11203,10524,11115,...& j: O( a* W8 l( |
    13320,16762,18673,20724,20803,21804];
# j, `9 u& J/ P2 ^, ~. {4 |p=[sqrs;sqjdcs;sqglmj];
. h/ @% A1 U" N1 i# ^$ [7 St=[glkyl;glhyl];) L* T  a6 }  e9 K
, F$ K4 x4 }/ n4 ]; e' ]
%数据归一化+ W- E8 f- q# {. C( f! P$ s1 T* e
[pn,ps1]=mapminmax(p);
3 d: d9 x2 V! x3 `% W: `[tn,ps2]=mapminmax(t);( k8 C8 Y# e* [" W/ u
+ p/ R9 x& S+ c/ _( L5 e" L& I$ g
%BP网络训练# {) C. g+ _7 O( }7 X$ O) y
net=newff(p,t,[3,7,2],{'tansig','tansig','purelin'},'traingdx');) F/ q4 s- p4 ?+ k
net.trainParam.show=1000;- t/ \: n) ~4 t, L9 ^
net.trainParam.Lr=0.05;4 x2 Y. _) g2 x6 t; K
net.trainParam.epochs=50000;
* j, B# [2 x& J1 V7 V$ x. ?net.trainParam.goal=0.65*10^(-3);. P( D4 ?4 L) T- w5 P
net=train(net,pn,tn);
$ l( r$ S, G2 H' n; D* k: h+ m2 q! U  x) c& M- H
%利用原数据对BP网络仿真$ v  i& ~+ y" _* z! j
an=sim(net,pn);+ y$ G( v. t# _! S- T, D* F
a=mapminmax('reverse',an,ps2);
" n% u+ f7 S) a: |9 S/ k1 O, o; S% d3 R. P
%仿真结果与原数据对比测试6 r, q  f& D" G& ~+ D
x=1990:2009;
5 N: J7 T8 ]& X3 o! G1 E. j5 bnewk=a(1,;
# g: |2 z0 k1 x7 v- N0 pnewh=a(2,;
1 L( K" c" Y8 q4 e; |# Q$ d+ c  e4 mfigure(2);/ g/ s& x( O' _5 T
subplot(2,1,1);plot(x,newk,'r-o',x,glkyl,'b--+');
' X4 `6 _- F/ M; t' L* q# H+ ]' klegend('网络输出客运量','实际客运量');
9 p6 U& A( k( _( Q1 S/ cxlabel('年份');ylabel('货运量、万人');
! J, P( @/ W, vtitle('运用工具箱客运量学习和测试对比图');
% @) v3 H  T( V* ?9 X1 }& Gsubplot(2,1,2);plot(x,newh,'r-o',x,glhyl,'b--+');8 X5 R- H4 m/ e
legend('网络输出货运量','实际货运量');3 z9 F2 U! D4 ?
xlabel('年份');ylabel('货运量、万吨');
, a. @% ]# J" L! C8 [title('运用工具箱货运量学习和测试对比图');" M$ p* ?# \9 _3 k  [7 V% i

' V" k7 B. F. q; U* r+ b) m8 l%新数据仿真( M2 X( k3 l: n" B9 ?! [( R
pnew=[73.39,75.55! u/ U' H, R, C9 j
    3.9635,4.0975  ^- O" z( p: Z3 u% r8 F) }
    0.9880,1.0268];% }$ K: ]9 K* _. e
pnewn=mapminmax('apply',pnew,ps1);9 a6 B2 w9 N  X; u  w7 ]6 t
anewn=sim(net,pnewn);# K' j4 g1 T! }+ {1 }% N7 f
anew=mapminmax('reverse',anewn,ps2)
: ~* V5 k3 W, A6 `$ k" \（修改的地方用颜色标记了）
0 C7 b% Q- Z  V' s6 N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
    % ?3 G: y5 e8 u, P0 e. y" |
  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 O# C$ c# f* p3 ~6 N% l5 B$ _
  3.     41.93,44.59,47.30,52.89,55.73,56.76,59.17,60.63];2 E. P( O5 W! X4 ^3 S* K6 n4 D- v& X
  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,...- y* [( C' X  N- J* ?
  5.     2.5,2.6,2.7,2.85,2.95,3.10];/ {5 J3 @+ R( D4 ^( h
  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,...# s: N0 C8 |% L; l. B3 Q
  7.     0.56,0.59,0.59,0.67,0.69,0.79];
    ) M2 k; h; C! F2 ]! P
  8. glkyl=[5126,6217,7730,9145,10460,11387,12353,15750,18304,19836,21024,19490,20433,...
    8 m& L, U8 S! Z& b, w2 t" D
  9.      22598,25107,33442,36836,40548,42927,43462];* a5 S$ K- x" ]3 U1 Q. E2 |1 {
  10. glhyl=[1237,1379,1385,1399,1663,1714,1834,4322,8132,8936,11099,11203,10524,11115,...
    6 c1 c# r4 l) T8 _" v2 k! D- [9 y6 C. r
  11.      13320,16762,18673,20724,20803,21804];
      W& v/ W' R8 E# `
  12. p=[sqrs;sqjdcs;sqglmj];
    . V6 {+ g' m2 \: p" t* z! S6 P5 o
  13. t=[glkyl;glhyl];
    0 z0 F/ Q7 i" K8 W% P
  14. %数据归一化- G; p! l# [) r, E7 ^" c
  15. [pn,ps1]=mapminmax(p);/ }  O6 O# c# |4 l8 h
  16. [tn,ps2]=mapminmax(t);
    / C. N+ s- j2 E9 I& w/ ]; G
  17. %dx=[-1,1;-1,1;-1,1];
    , {# E1 [* I7 t0 z0 b7 c
  18. [color=Red] p0=minmax(pn);t0=minmax(tn);[/color]
    " m; H8 e% p6 |; f
  19. + {( S' i  M1 _7 }. i. v  ?
  20. %BP网络训练
    5 X' O' C' u8 q3 X2 s! y6 u
  21. [color=Red] net=newff(p0,t0,[3,7,2],{'tansig','tansig','purelin'},'traingdx'); [/color]
    7 }& |$ b! I0 H$ {' U$ ?
  22. net.trainParam.show=1000;; Q; ^; ?9 H4 J, g. @. e
  23. net.trainParam.Lr=0.05;( f* i& b$ F# Z0 Q# }4 l1 K
  24. net.trainParam.epochs=50000;
    / z0 M+ a& Z; K: G1 e
  25. [color=Red] net.trainParam.goal=0.65*10^(-5);[/color]
      U" {! O" t+ I& n1 w
  26. net=train(net,pn,tn);
    ) \0 u7 e* m9 q9 q

  27. 9 Y: ?  r! v, V7 X) }& i4 @
  28. %利用原数据对BP网络仿真1 A! v* Q# [( d5 c/ L
  29. an=sim(net,pn);, H  z+ \+ e) V2 L
  30. a=mapminmax('reverse',an,ps2);. |! z7 \+ w0 S$ y. _9 l

  31. 1 w' G% o; K) D  \, Z; Q
  32. %仿真结果与原数据对比测试
    + s# U/ J! {) O
  33. x=1990:2009;2 O6 m$ T5 f( E0 Z; z3 a# T
  34. newk=a(1,:);7 [- ]" D' X, l$ o8 |1 c3 k/ b  d
  35. newh=a(2,:);
    ) Y3 Z" y% G# ?2 _, j: e8 l
  36. figure(2);1 B; ~/ ~  l2 s" k. R* l, H7 \
  37. subplot(2,1,1);plot(x,newk,'r-o',x,glkyl,'b--+');
    0 R0 B+ K2 B: F6 K0 M9 U# G- L
  38. legend('网络输出客运量','实际客运量');
    , u/ C" z+ V# a
  39. xlabel('年份');ylabel('货运量、万人');
    9 U, h7 z& u7 o6 N) }& [' }* q
  40. title('运用工具箱客运量学习和测试对比图');
    $ b. T4 E) `! {9 F
  41. subplot(2,1,2);plot(x,newh,'r-o',x,glhyl,'b--+');
    2 l' i. T$ [  \' d
  42. legend('网络输出货运量','实际货运量');" e) I- o) L& D1 y1 h/ J
  43. xlabel('年份');ylabel('货运量、万吨');$ m9 `: M. ~8 P# M4 M" a- C+ ^
  44. title('运用工具箱货运量学习和测试对比图');
    8 Z- K/ C7 F! T5 j4 ]+ W/ T
  45. 9 R" q! f$ ?! M, N  m3 S# l3 h
  46. %新数据仿真! ]5 X5 J0 w! n, y! G9 r) A; v
  47. pnew=[73.39,75.55$ K6 P8 I1 w9 G
  48.      3.9635,4.0975& f# m/ [( M9 C2 S- f2 h3 A: h' z) v
  49.      0.9880,1.0268];
    7 U; n, [1 @6 ?$ ~2 \! c
  50. pnewn=mapminmax('apply',pnew,ps1);
    , A% n7 @3 x4 p. F# h2 Z
  51. anewn=sim(net,pnewn);
    3 f0 W5 U2 r" F' W
  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. clc7 z6 Q" M% R, [( r1 {. u
  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,...
    ) e% \$ _3 V: c! h, f; h  \, s  l
  3.     41.93,44.59,47.30,52.89,55.73,56.76,59.17,60.63];
    " N8 u+ K" a# z6 A8 d# U! b
  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,.... a; C+ s! s7 h) b0 m4 @- ~- s
  5.     2.5,2.6,2.7,2.85,2.95,3.10];
    1 d; a2 G$ r( z, Q
  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,...
    , L9 i$ ?. F3 _7 v
  7.     0.56,0.59,0.59,0.67,0.69,0.79];8 o0 X, o& B9 v+ y# A
  8. glkyl=[5126,6217,7730,9145,10460,11387,12353,15750,18304,19836,21024,19490,20433,...; E% m, E5 P& C# Z
  9.      22598,25107,33442,36836,40548,42927,43462];
    / [- a! \) o0 ~8 ^. W
  10. glhyl=[1237,1379,1385,1399,1663,1714,1834,4322,8132,8936,11099,11203,10524,11115,...
    " t& L3 l9 E; D4 O
  11.      13320,16762,18673,20724,20803,21804];; f! v0 p2 i1 J7 W( E9 ~( e
  12. p=[sqrs;sqjdcs;sqglmj];
    , ^6 r6 X) B3 |; p( ]9 g" h
  13. t=[glkyl;glhyl];5 D( o5 G* C) I' }& A- E- p
  14. %数据归一化
    ! m) ]* t7 E% }3 U" R
  15. [pn,ps1]=mapminmax(p);
    - U9 Z( T) Q, U! ?5 `* ~4 Z
  16. [tn,ps2]=mapminmax(t);" I- G" R' e5 M7 E
  17. %dx=[-1,1;-1,1;-1,1];
    1 r6 O1 f3 Z4 x# Y) R9 C: z$ i
  18. p0=minmax(pn);t0=minmax(tn);! e; a. C; O6 D

  19. . H8 e* c/ j, ]: x; C$ Q
  20. %BP网络训练, L! s. i# z. l* ]1 d
  21. net=newff(p0,t0,[3,7,2],{'tansig','tansig','purelin'},'traingdx');
    9 ^7 Z$ b( A* G! S/ ~! W+ `7 t
  22. net.trainParam.show=1000;: N( k  I6 O4 v0 c) v
  23. net.trainParam.Lr=0.05;7 g& y% @  v7 O: m- v( \, }9 f
  24. net.trainParam.epochs=50000;4 n2 N& j- S3 ~4 r7 e; }/ c! ?7 f
  25. net.trainParam.goal=0.65*10^(-5);4 p2 u7 S4 w: e' G1 Z; s
  26. net=train(net,pn,tn);
    & }# {1 g+ `2 A# U( Q6 \9 a# ~

  27. - j/ T; x1 J& e' B0 E8 b  a2 E
  28. %利用原数据对BP网络仿真
    ; O! l( P: A! y% {  b8 L$ @& d
  29. an=sim(net,pn);
    ! j" ?* v' H2 N: Z! j9 r9 v
  30. a=mapminmax('reverse',an,ps2);
    2 p% Z4 |6 ?/ [# E. a4 ]0 j( R

  31. / z0 p, S& j' `' Z# Q1 t
  32. %仿真结果与原数据对比测试
    " u% a6 X) p7 |2 I! @
  33. x=1990:2009;
    5 _. f% ]* O8 t4 s( a6 L% L7 I/ t
  34. newk=a(1,:);  Q% a, G" b8 F+ w0 T
  35. newh=a(2,:);
    & x) ^( [8 C- Y" ~3 J
  36. figure(2);
    1 Z1 j% [9 s' t
  37. subplot(2,1,1);plot(x,newk,'r-o',x,glkyl,'b--+');* o- B# |# _1 q9 U2 Z
  38. legend('网络输出客运量','实际客运量');: G! Z: w- X. ^  d8 ~0 t
  39. xlabel('年份');ylabel('货运量、万人');
    5 @  W# E" M! ?" C1 o' R, p( B5 ]% O
  40. title('运用工具箱客运量学习和测试对比图');' k0 T& y5 E- r% I* s/ P( b
  41. subplot(2,1,2);plot(x,newh,'r-o',x,glhyl,'b--+');
    ( t1 w: M" p0 J* R! A4 a& |
  42. legend('网络输出货运量','实际货运量');
    7 ^7 t# g4 X' a( p
  43. xlabel('年份');ylabel('货运量、万吨');
    8 t8 p% i" X/ p; v( j2 H
  44. title('运用工具箱货运量学习和测试对比图');9 k! Q# X) ~2 Y+ W" x9 i) b
  45. 8 \! X9 Z  b0 ~% h- m. e
  46. %新数据仿真) L  O3 W  [+ H' h, r
  47. pnew=[73.39,75.55
    5 Q3 Q2 ]6 K7 s: t( O9 J- a! E
  48.      3.9635,4.0975
    / [: S1 K7 \8 n9 Y5 h3 R
  49.      0.9880,1.0268];
    # w) A  b3 E! Z2 {+ a9 O
  50. pnewn=mapminmax('apply',pnew,ps1);/ B% @8 K, b2 ^' n' b+ e. L% D
  51. anewn=sim(net,pnewn);0 z( t0 ]* [" o( x! [  f0 s
  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 ) X1 ]% H8 [5 P) A  Z, q
忽略我上面那个，改动的地方在18，21，25行……求批
6 u' |( Z" J; v2 M* `
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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作者: 且生    时间: 2014-7-22 23:35
  1. %BP网络训练
    4 m1 n2 u. b  A' O+ R  I: J
  2. net=newff(p0,t0,6,{'tansig'},'traingd');
    % h, g4 y6 t& c" y3 i! ~
  3. net.trainParam.show=1000;& R! M0 `5 X5 x2 t
  4. net.trainParam.Lr=0.05;
    ! F+ I' E+ Z6 ^& L9 ]' L
  5. net.trainParam.epochs=2000;4 {" O) v( [5 Q
  6. net.trainParam.goal=0.65*10^(-4);8 n4 _$ a, @" Q) H
  7. net=train(net,pn,tn);
复制代码
我只改了这里面的，; e# z0 u, ^4 E9 h7 E
一、改成单隐含层的，6个节点
- n9 u$ x) c5 w二、训练函数改成梯度下降BP算法 traingd
4 a; ^" E9 H1 j3 ~5 n: K5 Z4 z三、迭代次数改成2000& ]/ N6 i$ O5 u* E9 b
上面的参数是自己试的，我也不知道为什么。
! {8 o& n0 h' w% _( F; G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 |6 k5 s# d7 H* Y) n# P# F
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 4 C+ d; m% d7 A3 r# G8 H( @
你这例题是在什么书上找的？

; R. K( J6 ^: U7 C7 ~! }# L就是那本《matalb在数学建模中的应用》



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