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
modified.
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8 y6 G  |+ q$ p- ]) @Send suggestions to bkbirge@yahoo.com
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" R3 r# @' [: G' v; R5 K4 [! ~Updates will be posted periodically at the Mathworks User
Contributed Files website (www.mathworks.com) under the
Optimization category.

9 ~* T* h& y, k7 wTo install:
Extract into any directory you want but make sure the matlab
- [7 H2 O% t4 K/ G& E( L( \& Qpath points to that directory and the subdirectories
'hiddenutils' and 'testfunctions'.
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, ^: t! R# Y+ y# ?) ~( [! OEnjoy! - Brian Birge

, E9 i  R! a+ t& ^/ O( n-------------------------------------------------------------
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INFO
Quick start: just type ... out = pso_Trelea_vectorized('f6',2)
and 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
% `" ]) h5 c* Z/ T! x) e7 tenvironments. It can search for min, max, or 'distance' of
) |: h! B8 L+ Fuser developed cost function. Very easy to use and hack with
reasonably good documentation (type help for any function and
3 a# T# z( ~2 `9 P  bit should tell you what you need) and will take advantage of
6 D. o+ b; F1 k# @# yvectorized cost functions. It uses similar syntax to Matlab's
: C- ~6 a& S! T; r/ P1 goptimization toolbox. Includes a suite of static and dynamic
0 j$ Q' k: T  z& ~2 d: u) h1 V, |test functions. It also includes a dedicated PSO based neural
network trainer for use with Mathwork's neural network toolbox.
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$ J! \: G: u! j3 a/ w9 b# }0 N4 RRun 'DemoPSOBehavior' to explore the various functions, options,
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
# ~6 }  s( U; w. Lsuggestions. The main program 'pso_Trelea_vectorized.m' lists
8 }: [' u- y2 w4 K. E( Avarious 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,
+ N, k! d& i9 n9 ginvestigate Emergence, tune control systems/filters, paradigm
for multi-agent interaction, etc.

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0 C* |4 ~0 Z/ @9 K: O3 V4 y; ]Files included:


** in main directory:

- c$ F. V3 K& a' A# v3 B% y0) ReadMe.txt - this file, duh
' m  O1 b$ O. U1) 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
- Y) {: P( S2 d; A5 y3) 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.



** in 'hiddenutils'
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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
4 f& }+ p- M% v9 K2) 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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9 S8 Q; R* U& r6 Z+ V** in 'testfunctions'

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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Static test functions, minima don't change w.r.t. time/iteration:
+ o7 N9 J; X8 d( }" o4 h! J 1) Ackley
2) Alpine
% G7 s& J5 x3 {- T! Z 3) DeJong_f2
8 Y/ \! ?! e" p! O6 u" s 4) DeJong_f3
5) DeJong_f4
6) Foxhole
7) Griewank
0 I. P/ _# c2 A! O 8) NDparabola
9) Rastrigin
10) Rosenbrock
11) Schaffer f6
12) Schaffer f6 modified (5 f6 functions translated from each other)
13) Tripod

Dynamic test functions, minima/environment evolves over time (NOT iteration, though easily modifed to do so):
14) f6_bubbles_dyn
" z4 S) m( K0 c' h6 P15) f6_linear_dyn
& K  Y2 n  }5 Y" {6 V3 W: K16) f6_spiral_dyn
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7 x5 u) q2 f$ H5 p9 d** in 'nnet' (all these require Matlab's Neural Net toolbox)

1) demoPSOnet - standalone demo to show neural net training
2) trainpso   - the neural net toolbox plugin, set net.trainFcn to this
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(○^^)

1150865889

回复一个赚体力
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2268733244

太好用了，博主牛牛牛

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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