粒子群算法Matlab工具箱！

madio

PSOt, particle swarm optimization toolbox for matlab.
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, g; L9 h9 O8 {: U8 o/ ]May be distributed freely as long as none of the files are
; o' q, v. y7 smodified.
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Send suggestions to bkbirge@yahoo.com
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2 [0 ^4 c* f) p. K, X" [4 p0 _; jUpdates will be posted periodically at the Mathworks User
Contributed Files website (www.mathworks.com) under the
0 ^; L1 q- k" gOptimization category.

To install:
Extract into any directory you want but make sure the matlab
path points to that directory and the subdirectories
+ ]' m' N# K+ ^) M* F# z2 {'hiddenutils' and 'testfunctions'.

, v3 N. O4 |# {! r, I. ?Enjoy! - Brian Birge
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INFO
; J0 v5 T: J) J$ M9 |; r5 cQuick start: just type ... out = pso_Trelea_vectorized('f6',2)
) C, y0 ?& T, t: Nand watch it work!
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This is a PSO toolbox implementing Common, Clerc 1", and
Trelea types along with an alpha version of tracking changing
! ~0 _' X7 N0 o. z% X1 @% y0 a7 D% M1 X7 benvironments. It can search for min, max, or 'distance' of
user developed cost function. Very easy to use and hack with
reasonably good documentation (type help for any function and
. Z* q# m: K& R8 [  T( v3 dit should tell you what you need) and will take advantage of
% }9 h. w6 [$ i9 \! D! Cvectorized cost functions. It uses similar syntax to Matlab's
% q9 Y4 N6 m. H2 \' L1 Soptimization toolbox. Includes a suite of static and dynamic
. g4 Y/ u- ~8 ctest functions. It also includes a dedicated PSO based neural
: j  F* x0 S$ ^6 X# v- ?' s' Anetwork trainer for use with Mathwork's neural network toolbox.
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9 |9 ^& L4 d9 p. \8 l$ I/ uRun 'DemoPSOBehavior' to explore the various functions, options,
1 ~: u7 I9 V( o+ J' Nand visualizations.
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* c1 \! Z$ e* R& X" x# U/ nRun 'demoPSOnet' to see a neural net trained with PSO
(requires neural net toolbox).
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' _/ y. K2 V; LThis toolbox is in constant development and I welcome
2 C6 m% Q" E& N# csuggestions. The main program 'pso_Trelea_vectorized.m' lists
! j% U& R6 z1 ~3 e+ z; [) F+ H) Bvarious papers you can look at in the comments.

Usage ideas: to find a global min/max, to optimize training of
neural nets, error topology change tracking, teaching PSO,
investigate Emergence, tune control systems/filters, paradigm
for multi-agent interaction, etc.

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7 M" r- `  i  T# M' uFiles included:


+ E& G0 z3 c) _8 M( C  j** in main directory:

, C$ d! c! L, h0 s& r& j* k& {0) ReadMe.txt - this file, duh
5 ^1 L7 D5 G' g1) A Particle Swarm Optimization (PSO) Primer.pdf  -  powerpoint converted to pdf presentation explaining the very basics of PSO
' [" ~) O/ w/ M& ?2) DemoPSOBehavior.m - demo script, useful to see how the pso main function is called
' E' x( [/ }% W# X3) 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
/ s' `5 u1 k. u3 @8 [  r4) goplotpso.m - default plotting routine used by pso algorithm
8 A. j$ Z/ ~* _1 C1 v! c5) 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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' I( l6 z! `' [- s: C+ O** in 'hiddenutils'
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# V6 q, t0 r! m' M. Z6 k+ a+ D' Q1) 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
! E1 E5 b& h  F; V( H2) normmat.m - takes a matrix and reformats the data to fit between a new range, very flexible
( {- W5 }' ]& B/ _3) linear_dyn, spiral_dyn.m - helpers for the dynamic test functions listed in the 'testfunctions' directory
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; k6 |! u% v, r5 ^** in 'testfunctions'

+ g4 @8 t/ D% s2 B4 B. J. q6 q/ |- \. TA bunch of useful functions (mostly 2D) for testing. See help for each one for specifics. Here's a list of the names:

  ~% V) I6 n- T: d; _Static test functions, minima don't change w.r.t. time/iteration:
' b/ m. }3 v4 j; W! V 1) Ackley
4 V4 U: p( T# w5 K0 p 2) Alpine
# r% |5 L+ W" ^8 U. t5 f 3) DeJong_f2
4) DeJong_f3
5) DeJong_f4
4 ?( r( n, ?7 j" O 6) Foxhole
. n% F# y/ v9 ?6 {2 v& }1 d5 |5 f1 [  X 7) Griewank
5 \! M" A: F/ s2 F9 n 8) NDparabola
- G% X( f& n, A7 Y* z- s0 J 9) Rastrigin
0 c5 H6 e/ U; x$ C# U/ Z; K3 j4 W& o10) Rosenbrock
9 {% A- }- A/ m# b* }# Z11) Schaffer f6
12) Schaffer f6 modified (5 f6 functions translated from each other)
3 P1 x" I; t- z; a3 H* q% a13) Tripod

Dynamic test functions, minima/environment evolves over time (NOT iteration, though easily modifed to do so):
14) f6_bubbles_dyn
6 Q( c. Y7 [. W2 f* ~2 h15) f6_linear_dyn
16) f6_spiral_dyn

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** in 'nnet' (all these require Matlab's Neural Net toolbox)

1) demoPSOnet - standalone demo to show neural net training
0 L: C3 b% |+ Q/ H2 `3 w 2) trainpso   - the neural net toolbox plugin, set net.trainFcn to this
# R0 T! d3 r# m4 i 3) pso_neteval - wrapper used by trainpso to call the main PSO optimizer, this is the cost function that PSO will optimize
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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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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发表回看看感觉挺好用复
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