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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 q* W/ C% Z: B2 w. L3 F5 m; G7 G# l3 A
%原始数据输入" G( p9 ?% X( e0 s% O
clc
* b" V3 X' M! Y% U  ~) 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,...
1 a6 z+ _) w/ b9 e+ O. ^( J    41.93,44.59,47.30,52.89,55.73,56.76,59.17,60.63];
8 p- S8 Q2 L6 l5 V4 J0 Jsqjdcs=[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,...
- v( N: u- E8 H4 {4 Y    2.5,2.6,2.7,2.85,2.95,3.10];
- l* g5 U* f8 r, jsqglmj=[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,...
$ t' r) ~  Q2 ?* U0 K; ?% N6 I    0.56,0.59,0.59,0.67,0.69,0.79];
0 E1 C5 L2 f8 l  Q( K/ I5 Iglkyl=[5126,6217,7730,9145,10460,11387,12353,15750,18304,19836,21024,19490,20433,...
" f9 s% v7 j4 R; l6 W6 r+ L    22598,25107,33442,36836,40548,42927,43462];6 t  k- J3 J3 ^$ [
glhyl=[1237,1379,1385,1399,1663,1714,1834,4322,8132,8936,11099,11203,10524,11115,...
8 B' t3 }6 E+ b. k) ?    13320,16762,18673,20724,20803,21804];: @- W& s. I3 w' j* M) H; y3 ?
p=[sqrs;sqjdcs;sqglmj];/ R0 c* g4 o% R' c
t=[glkyl;glhyl];, o3 _% Z0 ]8 O' w; s
& f2 r/ g/ T" u+ S! V  t
%数据归一化* W4 `( t7 u0 c. b
[pn,ps1]=mapminmax(p);
( G2 J3 J0 N0 d7 H: b% L$ ][tn,ps2]=mapminmax(t);% Y& v- b- ]& D  x5 s) g  s6 K% S( x) L
dx=[-1,1;-1,1;-1,1];
. Y& d' b* @7 B5 ]1 q: R: U0 h; O- E0 X* Z) }$ W
%BP网络训练
: |- M3 G# @7 i  l; e" Vnet=newff(p,t,[3,7,2],{'tansig','tansig','purelin'},'traingdx');
9 c. c+ E4 ?5 t/ o+ }+ i4 m: Onet.trainParam.show=1000;
- F2 i$ o3 a4 E. y$ L: I" Z$ K6 Nnet.trainParam.Lr=0.05;
/ S" w$ Q! w' `" s! R! W2 mnet.trainParam.epochs=50000;0 D3 }4 `7 L! C$ x
net.trainParam.goal=0.65*10^(-3);5 M: K, g/ i0 I& `5 g6 @# \& Y
net=train(net,pn,tn);
5 _3 `5 x( m! N$ b# D6 }9 ~- ~5 l. c! v% K! A; s! I4 [
%利用原数据对BP网络仿真% M0 [# P" X$ r6 i9 v* |$ J" Y( y
an=sim(net,pn);/ d$ w" v% R$ i- R
a=mapminmax('reverse',an,ps2);
* o) F- `6 M8 U, P' y5 Y( ~, c/ g' h7 d+ z+ z
%仿真结果与原数据对比测试
' x6 X, f4 d/ |$ Cx=1990:2009;
9 V3 q/ G% D0 G( P+ L2 r% h- |& P" pnewk=a(1,:);# s8 E4 F; _$ m% E+ f4 `# V
newh=a(2,:);
7 J8 o8 ?; n! V- jfigure(2);
" q2 W5 Z) D, [# n9 l5 y) p" Jsubplot(2,1,1);plot(x,newk,'r-o',x,glkyl,'b--+');
% G* A, ~" L; u3 W3 o- Llegend('网络输出客运量','实际客运量');
5 Q. M' Q) N- j/ U- D" @  @xlabel('年份');ylabel('货运量、万人');. A: v5 R3 \1 c! X
title('运用工具箱客运量学习和测试对比图');
+ {# `0 g+ L9 x' vsubplot(2,1,2);plot(x,newh,'r-o',x,glhyl,'b--+');8 T0 x) L4 ~9 t4 Q* |
legend('网络输出货运量','实际货运量');7 U1 Y4 j  a7 O
xlabel('年份');ylabel('货运量、万吨');& e# z; b# _2 v, G9 v" F) }
title('运用工具箱货运量学习和测试对比图');
* i% T9 ~5 U% f1 o6 h: y" g8 ^% r2 V/ ]. N- M
%新数据仿真
! \8 f2 u- ?4 U4 F* x: O5 Dpnew=[73.39,75.55* B/ Y$ K/ ?3 u6 t# G2 M
    3.9635,4.0975, n7 o& ^. ~1 M! _' s
    0.9880,1.0268];
6 G$ I  J9 q! F$ g) ?pnewn=mapminmax('apply',pnew,ps1);& }7 C. @$ m/ a8 o; J
anewn=sim(net,pnewn);7 ~9 A  H# @! q* u) c0 \. l
anew=mapminmax('reverse',anewn,ps2)& w1 U7 W/ H/ U* _* z! Q1 Y' X

$ ~  @4 c. n0 |7 V

`VCWMZD9E$D~NHRR~AT9B4D.jpg (120.2 KB, 下载次数: 530)

`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 ! J3 S2 i- P8 i% n- @. d6 V
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 ...

7 z# D3 F' X% u" }) U因为版本更新，Matlab中的Newff命令用法有所改变，原命令为：+ t7 I9 i0 _3 n
net=newff(dx,[3,7,2]{'tansig','tansig','purelin'},'traingdx');
3 l# x! w. n! X" U我修改为：
5 @: N) Z0 ?7 P9 v/ Tnet=newff(p,t,[3,7,2],{'tansig','tansig','purelin'},'traingdx');: u2 w: q7 X+ T: u( ^) K/ r, x
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：
6 C; ~8 E* G# [3 X- a[pn,minp,maxp,tn,mint,maxt]=premnmx(p,t);
! O, ]' b& h/ r# za=postmnmx(an,mint,maxt);% Y' O$ R4 z4 _  S( E: z
pnewn=tramnmx(pnew,minp,maxp);
) b7 N4 T" j2 v8 `1 Fanew=postmnmx(anewn,mint,maxt)6 Y6 f+ ]8 o7 e+ g; L' ^! R
我修改为：5 t! T1 D8 w% ~, r! _# a
[pn,ps1]=mapminmax(p);[tn,ps2]=mapminmax(t);
8 S9 x9 w7 U5 W' m7 Ra=mapminmax('reverse',an,ps2);
, Y) C/ B) a6 mpnewn=mapminmax('apply',pnew,ps1);
- d. ?# p1 J# z- K5 f( T" H0 T! Danew=mapminmax('reverse',anewn,ps2)- \9 a: k$ B/ k( U
8 Y" C0 R7 I; }7 ]* d
原程序为：
8 _5 R) T/ u9 I4 a1 l$ f%原始数据输入' u" o' I* H/ {$ G* I' P
clc# z5 q: J) O4 \) E# e! ^0 |
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,...3 a! Q5 S5 @! t$ t
    41.93,44.59,47.30,52.89,55.73,56.76,59.17,60.63];& r* v$ F  s$ e/ O' W9 q* l5 G3 o. |
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; Q) Y% g2 u/ c9 J$ `    2.5,2.6,2.7,2.85,2.95,3.10];4 n% P3 ~7 H2 x- P" G9 R( Y) V9 i
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- x, J4 J9 ~( r3 p, g
    0.56,0.59,0.59,0.67,0.69,0.79];
* @1 n. v. u4 ~8 F" B7 E7 ]' V1 o: cglkyl=[5126,6217,7730,9145,10460,11387,12353,15750,18304,19836,21024,19490,20433,...
1 _0 J5 v0 H4 K, W- e6 Y    22598,25107,33442,36836,40548,42927,43462];9 g8 V$ f/ d: }/ L
glhyl=[1237,1379,1385,1399,1663,1714,1834,4322,8132,8936,11099,11203,10524,11115,...
; |6 K( m) ~8 V4 c* e; U) A2 ^    13320,16762,18673,20724,20803,21804];# R; j/ X. z4 h4 }2 ?$ h  o# }
p=[sqrs;sqjdcs;sqglmj];
+ `  v8 d( H  A6 dt=[glkyl;glhyl];
- g$ N  m/ f4 h6 I' W
: b, T- [" t) V7 J6 G%数据归一化
' V! o. K+ ~! ]! a7 _# M; M[pn,minp,maxp,tn,mint,maxt]=premnmx(p,t);! i& f+ U; M5 p0 W2 M
dx=[-1,1;-1,1;-1,1];9 J# N& c! \" @

: P: L! @5 w- V" v%BP网络训练
$ z: w- D& c2 u4 cnet=newff(dx,[3,7,2],{'tansig','tansig','purelin'},'traingdx');% s' m9 j6 D* p  p! g
net.trainParam.show=1000;& z( F& ]: ^" ]* N+ }. k3 r3 q
net.trainParam.Lr=0.05;" K  y, B4 |' Z0 W9 M# J
net.trainParam.epochs=50000;
  g/ Q. m( r* B8 Snet.trainParam.goal=0.65*10^(-3);
! J, s7 `6 }5 B6 i+ l. k: h: _4 znet=train(net,pn,tn);
. N3 O1 e8 ]9 @1 H+ I( u
9 A$ G; a2 h+ Q6 @& s1 S7 y%利用原数据对BP网络仿真5 Y+ z5 ]/ g3 r
an=sim(net,pn);+ T" Y+ m  X/ X0 B; ^2 s
a=postmnmx(an,mint,maxt);" w  O" d6 x, X2 N# S' K; ~

+ y: P# y3 N4 w& R$ v%仿真结果与原数据对比测试
* O# P5 H1 Z% G& p" j5 Q! D, G8 _x=1990:2009;
1 M! p& s% }) c  wnewk=a(1,;2 c4 L6 `7 a# ]: z5 a* U6 L
newh=a(2,;5 i0 M5 c+ |* N) s
figure(2);
. J& s) K  N8 S  D1 ~subplot(2,1,1);plot(x,newk,'r-o',x,glkyl,'b--+');
% p( p, Y0 q# m* x+ S% [legend('网络输出客运量','实际客运量');- N# e9 [7 ^- T% V) N; d1 K
xlabel('年份');ylabel('货运量、万人');* |, k$ G( C2 L% r
title('运用工具箱客运量学习和测试对比图');/ Y: [) p, A' k6 ]  Y+ ~
subplot(2,1,2);plot(x,newh,'r-o',x,glhyl,'b--+');5 ?  W, O9 \) y) r5 Z6 v
legend('网络输出货运量','实际货运量');$ t3 d2 Y. ^* d
xlabel('年份');ylabel('货运量、万吨');
: _2 [) t, A: W; R6 ^title('运用工具箱货运量学习和测试对比图');
, r- h  q. b/ ]6 I5 F! h" G6 `8 q, v, m8 B
%新数据仿真( _% ]- G0 b/ j6 e% z: v8 @- g: c% X
pnew=[73.39,75.55
6 X4 p/ _$ z! P# F0 o0 k    3.9635,4.09750 u$ c: V3 A: s! |- L1 x
    0.9880,1.0268];: n+ U+ G8 a) M1 o
pnewn=tramnmx(pnew,minp,maxp);! t7 T- |" ]1 M1 o* l" Z; B+ e
anewn=sim(net,pnewn);2 _; r. n2 k% `# l4 {8 W" s: E: N$ I
anew=postmnmx(anewn,mint,maxt)
3 S# _, k" k  Q1 _2 x- f- p9 S8 E/ _
修改后程序为：" d+ Y* J. _, e/ v% S
%原始数据输入4 M& c2 q7 N6 j, p5 e/ e' h* f
clc/ A9 \# g% K# W+ K
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 ~5 ?" `' H0 t" \4 a
    41.93,44.59,47.30,52.89,55.73,56.76,59.17,60.63];
" |7 Q8 ]  `5 f! Lsqjdcs=[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,...
  E9 M' M2 x& w* Y: C5 J    2.5,2.6,2.7,2.85,2.95,3.10];
% P0 F$ d/ N0 F! }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,..., g2 [# A; v0 O7 }
    0.56,0.59,0.59,0.67,0.69,0.79];, M- `9 c; m# u
glkyl=[5126,6217,7730,9145,10460,11387,12353,15750,18304,19836,21024,19490,20433,...
* O; x! R6 a. ^; W    22598,25107,33442,36836,40548,42927,43462];) `$ x: I1 i" ]5 b
glhyl=[1237,1379,1385,1399,1663,1714,1834,4322,8132,8936,11099,11203,10524,11115,...2 V" K; y7 C1 r: D! z
    13320,16762,18673,20724,20803,21804];
9 G0 \/ P! I* R) y6 `p=[sqrs;sqjdcs;sqglmj];
9 y1 M: N. Y8 L6 ^8 P9 g. Jt=[glkyl;glhyl];/ U& w. v& D% d% l) Q, B! V
: w& X$ [9 ^# m' [9 o
%数据归一化5 {4 X0 i" ~& H8 J* f
[pn,ps1]=mapminmax(p);
2 H/ C, p1 k3 R[tn,ps2]=mapminmax(t);
4 A- f0 Q+ |" x
8 p3 T8 Q0 u% |8 A3 S%BP网络训练
* |, F+ ]6 B4 |6 x$ jnet=newff(p,t,[3,7,2],{'tansig','tansig','purelin'},'traingdx');
1 z! k3 ]) d1 @0 n; Gnet.trainParam.show=1000;& q! R" y* Q+ s. n' |
net.trainParam.Lr=0.05;
  q3 O. ^; C% f6 R( x. jnet.trainParam.epochs=50000;
3 x( |- l) h4 ^) |net.trainParam.goal=0.65*10^(-3);
9 t* F# ]# ^/ C2 fnet=train(net,pn,tn);
. l! e, z% z( r" H* `  ]8 r" J4 u1 L. L, `& m& W- i" V
%利用原数据对BP网络仿真
% u0 c2 {; n5 A0 l) W7 L' \( z+ _an=sim(net,pn);
$ {3 |$ U% h, P! _- S0 u7 E6 O9 m5 Oa=mapminmax('reverse',an,ps2);  W2 ?/ V" }8 w; g
( D  e2 c; S6 f6 a, `1 ], `
%仿真结果与原数据对比测试- w, j. o) |0 \+ i2 n
x=1990:2009;7 a  }6 \5 ~/ W1 Z) u- M0 v/ F
newk=a(1,;- A0 z2 j- i2 n% N$ ~. m
newh=a(2,;
1 [/ \% o- I0 K% A# Y+ W1 Zfigure(2);
5 p+ u) D- b! M0 I# h: d* usubplot(2,1,1);plot(x,newk,'r-o',x,glkyl,'b--+');
, U" U0 d+ t  q4 _2 g& {' ?legend('网络输出客运量','实际客运量');! ?% Q7 I0 t) z
xlabel('年份');ylabel('货运量、万人');
, L4 L4 Q& [" G' o4 ~; Ntitle('运用工具箱客运量学习和测试对比图');
/ I! L9 m4 D; K' {4 d/ j4 E, w9 Zsubplot(2,1,2);plot(x,newh,'r-o',x,glhyl,'b--+');
1 p. v4 I# m+ E! R2 Ilegend('网络输出货运量','实际货运量');! u5 q( R0 J0 Q$ A* N1 b" I+ t
xlabel('年份');ylabel('货运量、万吨');
" V$ v$ @+ i, f( u& Stitle('运用工具箱货运量学习和测试对比图');) H$ W+ n& M4 C" N

9 p. l7 q1 [3 H4 N  o$ y7 w  W  {%新数据仿真  U, q+ n4 _2 P& Z& S7 Q
pnew=[73.39,75.55
. V' c5 E) V# r2 Q2 c! t, ]    3.9635,4.09758 y8 B2 d* |" x7 H. J
    0.9880,1.0268];1 N( p8 N: q0 B6 J. A
pnewn=mapminmax('apply',pnew,ps1);2 c% t" E# o/ Q7 J
anewn=sim(net,pnewn);
, Q: g% m9 c& Q: e( p' b8 s) Vanew=mapminmax('reverse',anewn,ps2)
8 r6 O* m$ }5 @1 }3 e+ }8 ~3 @（修改的地方用颜色标记了）3 j$ A' P) j5 d# w+ J) A" 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
    1 X. n  T  r, q7 k3 n, z2 [4 b& ]' 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,...
    8 Q, @; j/ x$ ~! i( q! _8 O
  3.     41.93,44.59,47.30,52.89,55.73,56.76,59.17,60.63];
    8 }& r% _7 d4 Y0 s. Y+ H2 [
  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,...
    / S/ e3 m$ B7 i$ Q' c* T
  5.     2.5,2.6,2.7,2.85,2.95,3.10];
    ! X+ S! _0 v& Y5 t! 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,...
    ! C3 W% P  M9 D8 X
  7.     0.56,0.59,0.59,0.67,0.69,0.79];
      o! B: `# ]2 f
  8. glkyl=[5126,6217,7730,9145,10460,11387,12353,15750,18304,19836,21024,19490,20433,...
    0 }  ~3 z& p. l1 K
  9.      22598,25107,33442,36836,40548,42927,43462];2 d7 e. {; r: c. U9 z3 N& e0 V
  10. glhyl=[1237,1379,1385,1399,1663,1714,1834,4322,8132,8936,11099,11203,10524,11115,...
    , c7 T* b, @/ ?$ v
  11.      13320,16762,18673,20724,20803,21804];
    . q" O) x8 d; x+ N6 }( o
  12. p=[sqrs;sqjdcs;sqglmj];2 F* k: p. P6 \# ?/ ^8 O
  13. t=[glkyl;glhyl];
    ' O& g8 @. n; A" \% Z4 d
  14. %数据归一化
    , k9 L' P4 q, O$ {; Y2 |) A
  15. [pn,ps1]=mapminmax(p);
    6 Z# [. i2 ~7 H) k' D' r3 Q
  16. [tn,ps2]=mapminmax(t);0 Y" V1 \# G8 k; P% m$ ]
  17. %dx=[-1,1;-1,1;-1,1];/ W1 L  e1 }" o4 \$ _5 A' j6 ^
  18. [color=Red] p0=minmax(pn);t0=minmax(tn);[/color]
    / Y' i! _1 ^" \7 R, Q0 N. ?
  19. $ Q0 T: s( S* M/ ~* ?
  20. %BP网络训练
    $ g+ j- }" e; D% E# ]& X. p
  21. [color=Red] net=newff(p0,t0,[3,7,2],{'tansig','tansig','purelin'},'traingdx'); [/color]! G% m0 {" Z1 u$ b/ C5 s. n
  22. net.trainParam.show=1000;6 B/ v2 @4 Q3 A* X! I* ]$ j
  23. net.trainParam.Lr=0.05;7 e9 z0 ?4 t2 e
  24. net.trainParam.epochs=50000;3 u, g1 \- j. }
  25. [color=Red] net.trainParam.goal=0.65*10^(-5);[/color]
    ' X2 P/ U, j6 U' I7 Z
  26. net=train(net,pn,tn);9 M% F5 ^  S9 j3 z, g: t3 V

  27. 6 s& K" x% h  h4 M) {8 m& F# i# {
  28. %利用原数据对BP网络仿真
    9 Q1 @) \! p, N; U& g( A
  29. an=sim(net,pn);
    % `3 _+ R* f+ @
  30. a=mapminmax('reverse',an,ps2);
    " u" [# U  ?/ V4 I7 Q

  31. . c  H5 G& l( S3 i) m
  32. %仿真结果与原数据对比测试 9 [$ i$ A7 e4 l
  33. x=1990:2009;
    2 m( g5 B/ L( M) _: X
  34. newk=a(1,:);. w+ e" b8 P, c' `
  35. newh=a(2,:);
    / A# g/ ]0 u, Q
  36. figure(2);
    ( X) J4 M8 |' f7 F# ~: O
  37. subplot(2,1,1);plot(x,newk,'r-o',x,glkyl,'b--+');
    . _' B1 i6 m4 e- h4 r( ~7 j* f
  38. legend('网络输出客运量','实际客运量');
    & Q" n# Q( S! G+ K) m+ b$ u1 G
  39. xlabel('年份');ylabel('货运量、万人');/ B$ K3 {, r* f4 e
  40. title('运用工具箱客运量学习和测试对比图');1 S5 ]; ?0 `0 U* P5 V+ R
  41. subplot(2,1,2);plot(x,newh,'r-o',x,glhyl,'b--+');6 s' z: ^& @7 I* j0 t( u5 e2 E7 q; u
  42. legend('网络输出货运量','实际货运量');1 [, g7 t, g" |: P7 g* L. M4 X: C2 m
  43. xlabel('年份');ylabel('货运量、万吨');
    3 v  C% Z+ M# S- ]/ r& A: J8 t% I  |
  44. title('运用工具箱货运量学习和测试对比图');. A& H0 {3 R. J" K, P
  45. / J  K" r! F: p+ o) G1 |
  46. %新数据仿真9 F* |6 ^! S# D0 I4 t
  47. pnew=[73.39,75.55. Y% a7 v# s& e, U7 M
  48.      3.9635,4.0975
    " s  c0 U/ \, \! i2 d) P7 h
  49.      0.9880,1.0268];
    ) D! K" }0 Z& Q5 H; i/ `
  50. pnewn=mapminmax('apply',pnew,ps1);. D9 V) n2 o5 u) B" t& Q
  51. anewn=sim(net,pnewn);
    - Y! _% ?6 B3 r% r
  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. clc9 J1 ~% @6 y/ ^1 x. x; s3 Y, L% 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,...
    4 b* m# G+ k; K9 j* }( ]
  3.     41.93,44.59,47.30,52.89,55.73,56.76,59.17,60.63];
    & s8 g! A5 n% A- [+ 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,..." _# G* d4 i- f; o: P9 g. N+ O
  5.     2.5,2.6,2.7,2.85,2.95,3.10];6 G1 g5 O+ ^, E  O8 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,...  m+ C8 U! E3 K5 W
  7.     0.56,0.59,0.59,0.67,0.69,0.79];" S. _3 x& E" ]/ U1 I8 z# C' \
  8. glkyl=[5126,6217,7730,9145,10460,11387,12353,15750,18304,19836,21024,19490,20433,...# y5 y* N/ w) ^8 v6 }6 S6 L$ @6 y9 w
  9.      22598,25107,33442,36836,40548,42927,43462];
    % ~- `, [7 i! W5 H
  10. glhyl=[1237,1379,1385,1399,1663,1714,1834,4322,8132,8936,11099,11203,10524,11115,...
    / U$ g! n& j" U5 R* |# Q2 C9 O0 O+ W
  11.      13320,16762,18673,20724,20803,21804];* ~; L' C. P+ i9 A8 X
  12. p=[sqrs;sqjdcs;sqglmj];
    4 D0 N+ o0 o  O; }
  13. t=[glkyl;glhyl];4 b5 f- _* x' u, x/ D
  14. %数据归一化
    2 |7 b* ~# M3 u, _' C
  15. [pn,ps1]=mapminmax(p);! f$ Z1 [% U; A( l: u
  16. [tn,ps2]=mapminmax(t);
    " h$ L8 `! i9 [1 `
  17. %dx=[-1,1;-1,1;-1,1];
    7 A# K; J! o' v4 h5 A6 R; ^! F
  18. p0=minmax(pn);t0=minmax(tn);) A- l; h+ X: j2 e

  19. 8 b. m+ W; L# ?& W/ b4 D- ~5 R
  20. %BP网络训练- z% @3 ?* N" e9 n$ P) P3 a
  21. net=newff(p0,t0,[3,7,2],{'tansig','tansig','purelin'},'traingdx'); , {; M6 K2 {8 c& U( Q+ g
  22. net.trainParam.show=1000;
    8 j" q" q8 ^% Q5 O
  23. net.trainParam.Lr=0.05;' j" c$ S9 N0 L; m
  24. net.trainParam.epochs=50000;
    4 ?" u, E' c, x% Z: ?' b  }" ]
  25. net.trainParam.goal=0.65*10^(-5);
    * {0 z' g8 m' M* ~" ~9 I* l& D
  26. net=train(net,pn,tn);
    ( k! [, g4 e$ O  b1 o8 _$ {
  27. ( A  w) m; ^0 B4 J) \8 P
  28. %利用原数据对BP网络仿真
    ' {; U5 i" u: \6 N; l
  29. an=sim(net,pn);
    $ Q: X* n" Z# V5 y) Z9 [8 [# L( @
  30. a=mapminmax('reverse',an,ps2);+ J' B5 y; p0 x# Q; K

  31. ) b/ Y6 r* Z2 y9 D% @: C
  32. %仿真结果与原数据对比测试
    2 Z- L( S4 t3 N; |  U6 N* E4 ^8 P
  33. x=1990:2009;6 H( W7 P1 m* d5 @
  34. newk=a(1,:);9 u$ S0 V" f# N' {& q
  35. newh=a(2,:);
    & c& ], U  H' D( O
  36. figure(2);
    " }7 ^4 k, b: W
  37. subplot(2,1,1);plot(x,newk,'r-o',x,glkyl,'b--+');
    3 a0 l6 P; {7 M+ m  H+ a
  38. legend('网络输出客运量','实际客运量');4 d5 e; i1 P; y- M
  39. xlabel('年份');ylabel('货运量、万人');
    6 i8 e- [. H- N  W2 @
  40. title('运用工具箱客运量学习和测试对比图');
    & H; M! c7 W; j
  41. subplot(2,1,2);plot(x,newh,'r-o',x,glhyl,'b--+');( ^/ U! P( o, s/ N' z
  42. legend('网络输出货运量','实际货运量');+ P7 L4 K4 ^0 z: L7 M8 [* m' z
  43. xlabel('年份');ylabel('货运量、万吨');
    0 e2 ?5 T4 f+ J2 y
  44. title('运用工具箱货运量学习和测试对比图');
    6 V: E8 s* Q& Q1 e* k6 a4 p
  45. 0 j1 T+ V, t- x# X
  46. %新数据仿真
    : I7 X- o1 V8 B% v! j6 b, y9 y
  47. pnew=[73.39,75.55( K0 F- Z2 m+ b4 I" p
  48.      3.9635,4.0975
    % D( {) u) x1 U$ o; `4 _, K
  49.      0.9880,1.0268];
    + X+ Q/ d& Y3 Y" N
  50. pnewn=mapminmax('apply',pnew,ps1);7 ~+ ?7 V) Y4 z
  51. anewn=sim(net,pnewn);0 X0 T4 w" {' ]# A& f# b' v
  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 " }/ m* M. k, T. I6 \1 h
忽略我上面那个，改动的地方在18，21，25行……求批
$ l3 ^, |! N8 a/ J9 i
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

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p2.jpg

作者: 且生    时间: 2014-7-22 23:35
  1. %BP网络训练
    ' ?( p  |$ ~' K- q5 w* x( @- \) L
  2. net=newff(p0,t0,6,{'tansig'},'traingd');
    % u2 B& {6 |& L! B( J+ W- ~7 r
  3. net.trainParam.show=1000;
    / a/ A, p  g4 Z1 f  @
  4. net.trainParam.Lr=0.05;3 _/ Z* A2 m4 Z) [
  5. net.trainParam.epochs=2000;" _& I+ C( \) j. T+ N1 X# O# @
  6. net.trainParam.goal=0.65*10^(-4);
      T+ U+ _! R% V& H  s1 I/ L
  7. net=train(net,pn,tn);
复制代码
我只改了这里面的，
9 o6 m# f) d2 |7 Y% s一、改成单隐含层的，6个节点
" Z/ b% W' B- Q  ]. Q. b/ N二、训练函数改成梯度下降BP算法 traingd" H1 @/ c- n+ C% X
三、迭代次数改成2000
; r" e3 e: U. D5 V& a* Q  t1 M6 J上面的参数是自己试的，我也不知道为什么。
2 |8 u, L' n  y, 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。
: X$ p6 L8 z, N. y3 o! a/ I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 % R6 v8 F5 h1 B4 ]
你这例题是在什么书上找的？

. i) M1 x2 r) D# S5 B9 n/ {就是那本《matalb在数学建模中的应用》



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