粒子群算法Matlab工具箱！

madio

PSOt, particle swarm optimization toolbox for matlab.
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May be distributed freely as long as none of the files are
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Send suggestions to bkbirge@yahoo.com

Updates will be posted periodically at the Mathworks User
Contributed Files website (www.mathworks.com) under the
/ W- K( o7 x* R! XOptimization category.

0 K) I# B* @! ~5 J3 h8 M+ H0 \To install:
0 V8 e( y7 i# s" @4 W- d9 BExtract into any directory you want but make sure the matlab
path points to that directory and the subdirectories
; \2 u6 i8 v! U3 ]8 m1 T; q( o'hiddenutils' and 'testfunctions'.

9 O% Y+ B  c1 ]0 s  Z/ pEnjoy! - Brian Birge
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, m8 l3 \, l2 N) n' }-------------------------------------------------------------
  \7 y6 w0 o" a* g! L-------------------------------------------------------------
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INFO
0 ^! A* c1 N8 ]3 o% jQuick start: just type ... out = pso_Trelea_vectorized('f6',2)
3 x7 Y, K8 \; a- n& @0 B% Nand watch it work!

This is a PSO toolbox implementing Common, Clerc 1", and
Trelea types along with an alpha version of tracking changing
environments. It can search for min, max, or 'distance' of
: m/ j. `: H( G1 [user developed cost function. Very easy to use and hack with
- }* l: S" j! areasonably good documentation (type help for any function and
( X" E, _4 W8 ?+ y- ]  R' u. |+ S/ r% U" Ait should tell you what you need) and will take advantage of
vectorized cost functions. It uses similar syntax to Matlab's
2 A, P& f' Y; u) ^optimization toolbox. Includes a suite of static and dynamic
5 M# L  g: v$ d/ m1 G% Ytest functions. It also includes a dedicated PSO based neural
# j3 r" {$ M7 q: t0 _- D" o0 }- \network trainer for use with Mathwork's neural network toolbox.

Run 'DemoPSOBehavior' to explore the various functions, options,
; N6 {$ s+ F) K4 r* t9 m- ]and visualizations.

Run 'demoPSOnet' to see a neural net trained with PSO
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This toolbox is in constant development and I welcome
0 u" E% a1 g! j# b* fsuggestions. The main program 'pso_Trelea_vectorized.m' lists
! a/ {: Y4 H5 u( F8 v. y# Avarious papers you can look at in the comments.
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: k7 |1 b( n- [; K. E) k9 ]Usage ideas: to find a global min/max, to optimize training of
$ I( K# v6 c9 g  nneural nets, error topology change tracking, teaching PSO,
3 Q% p5 J$ g# E( |0 {& b! vinvestigate Emergence, tune control systems/filters, paradigm
: T, }! C6 V& B" D8 D  bfor multi-agent interaction, etc.

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Files included:

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** in main directory:

' L( p& [% C5 W9 \! V+ V: \/ O0) ReadMe.txt - this file, duh
) F. [. ]) O+ Y" g8 v1) A Particle Swarm Optimization (PSO) Primer.pdf  -  powerpoint converted to pdf presentation explaining the very basics of PSO
2) DemoPSOBehavior.m - demo script, useful to see how the pso main function is called
3) goplotpso4demo.m - plotting routine called by the demo script, useful to see how custom plotting can be developed though this routine slows down the PSO a lot
4) goplotpso.m - default plotting routine used by pso algorithm
5) pso_Trelea_vectorized.m - main PSO algorithm function, implements Common, Trelea 1&2, Clerc 1", and an alpha version of tracking environmental changes.

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** in 'hiddenutils'

1) forcerow, forcecol.m - utils to force a vector to be a row or column, superseded by Matlab 7 functions I believe but I think they are still called in the main algo
2) normmat.m - takes a matrix and reformats the data to fit between a new range, very flexible
3) linear_dyn, spiral_dyn.m - helpers for the dynamic test functions listed in the 'testfunctions' directory

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** in 'testfunctions'
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A bunch of useful functions (mostly 2D) for testing. See help for each one for specifics. Here's a list of the names:
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" b3 g( H- `6 }3 z) a7 WStatic test functions, minima don't change w.r.t. time/iteration:
1) Ackley
2) Alpine
) |: z) c3 o4 X: n( I; ^5 X 3) DeJong_f2
( K) T& t( p: F; A 4) DeJong_f3
5) DeJong_f4
5 K# E) v7 a" @# k/ z! N" E4 v 6) Foxhole
7) Griewank
. q% R, a# s& P6 N& t 8) NDparabola
. I& V. |4 x0 s) |# o 9) Rastrigin
" c9 }: R* u; H! O% O3 X* j10) Rosenbrock
! l* b1 ^1 D, Y" Q* v11) Schaffer f6
2 [: `, e7 @7 k( O7 K1 K9 ^0 E12) Schaffer f6 modified (5 f6 functions translated from each other)
( `+ R* F9 m2 \& I13) Tripod

! h% ?' V$ Q) c, eDynamic test functions, minima/environment evolves over time (NOT iteration, though easily modifed to do so):
& o' C9 @2 w2 [14) f6_bubbles_dyn
7 v+ l- @6 k7 D$ [+ t; u( g) Z15) f6_linear_dyn
0 ^# B. r, b; P; T4 }4 f) K16) f6_spiral_dyn
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** in 'nnet' (all these require Matlab's Neural Net toolbox)

7 P% J& m/ t7 N; `/ Y$ \ 1) demoPSOnet - standalone demo to show neural net training
2) trainpso   - the neural net toolbox plugin, set net.trainFcn to this
- [! x) ?9 }( X( ]/ S 3) pso_neteval - wrapper used by trainpso to call the main PSO optimizer, this is the cost function that PSO will optimize
5 g: y8 i% Z% a 4) goplotpso4net - default graphing plugin for trainpso, shows net architecture, relative weight indications, error, and PSO details on run

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枫叶下的你

发表回复嗯嗯嗯ヽ(○^^)
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1150865889

回复一个赚体力

2268733244

太好用了，博主牛牛牛
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932624145

感觉很不错的

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57475207

发表回看看感觉挺好用复
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