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PSOt, particle swarm optimization toolbox for matlab.
May be distributed freely as long as none of the files are
modified.
Send suggestions to bkbirge@yahoo.com
Updates will be posted periodically at the Mathworks User
Contributed Files website (www.mathworks.com) under the
Optimization category.
To install:
Extract into any directory you want but make sure the matlab
path points to that directory and the subdirectories
'hiddenutils' and 'testfunctions'.
Enjoy! - Brian Birge
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INFO
Quick start: just type ... out = pso_Trelea_vectorized('f6',2)
and 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
user developed cost function. Very easy to use and hack with
reasonably good documentation (type help for any function and
it should tell you what you need) and will take advantage of
vectorized cost functions. It uses similar syntax to Matlab's
optimization toolbox. Includes a suite of static and dynamic
test functions. It also includes a dedicated PSO based neural
network trainer for use with Mathwork's neural network toolbox.
Run 'DemoPSOBehavior' to explore the various functions, options,
and visualizations.
Run 'demoPSOnet' to see a neural net trained with PSO
(requires neural net toolbox).
This toolbox is in constant development and I welcome
suggestions. The main program 'pso_Trelea_vectorized.m' lists
various 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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Files included:
** in main directory:
0) ReadMe.txt - this file, duh
1) 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.
** 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
** 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:
Static test functions, minima don't change w.r.t. time/iteration:
1) Ackley
2) Alpine
3) DeJong_f2
4) DeJong_f3
5) DeJong_f4
6) Foxhole
7) Griewank
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
15) f6_linear_dyn
16) f6_spiral_dyn
** 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
没有合适的资源?快使用搜索试试~ 我知道了~
Matlab系列--机器学习及其matlab实现.zip
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Matlab系列--机器学习及其matlab实现.zip (439个子文件)
svmtrain.c 11KB
svmpredict.c 9KB
svm_model_matlab.c 8KB
qsort.c 5KB
qsort.c 5KB
libsvmread.c 4KB
libsvmwrite.c 2KB
Compile_Check 856B
Compile_Check_kcachegrind 611B
Compile_Check_memcheck 623B
COPYRIGHT 1KB
svm.cpp 61KB
reg_RF.cpp 39KB
classRF.cpp 33KB
mex_regressionRF_train.cpp 12KB
diabetes_C_wrapper.cpp 11KB
twonorm_C_wrapper.cpp 10KB
rfutils.cpp 9KB
classTree.cpp 9KB
mex_ClassificationRF_train.cpp 8KB
cokus.cpp 7KB
cokus.cpp 7KB
mex_ClassificationRF_predict.cpp 5KB
mex_regressionRF_predict.cpp 4KB
cokus_test.cpp 1KB
cokus_test.cpp 1KB
data.csv 204B
twonorm_C_devcpp.dev 2KB
diabetes_C_devc.dev 1KB
picture1.eps 101KB
rfsub.f 15KB
f_Rastrigrin_10d20p 900B
f_Rastrigrin_10d40p 900B
f_Rastrigrin_10d80p 900B
f_Rastrigrin_20d20p 900B
f_Rastrigrin_20d40p 900B
rf.h 5KB
svm.h 3KB
reg_RF.h 560B
svm_model_matlab.h 201B
h_Rastrigrin_10d20p 802B
h_Rastrigrin_10d40p 802B
h_Rastrigrin_10d80p 802B
h_Rastrigrin_20d20p 802B
h_Rastrigrin_20d40p 802B
Example_1.html 25KB
Example_2.html 19KB
main.html 18KB
main_GRNN_PNN.html 17KB
main.html 16KB
main.html 16KB
main.html 15KB
ga_bp.html 13KB
main.html 12KB
main.html 10KB
main.html 10KB
PCR_Demo.html 10KB
main.html 10KB
main.html 10KB
main_iris.html 9KB
PLS_Demo.html 9KB
main_spectra.html 9KB
main.html 8KB
SA_GUI_demo.html 8KB
main_RBF.html 8KB
main.html 7KB
pso.m 25KB
pso_Trelea_vectorized.m 22KB
classRF_train.m 14KB
regRF_train.m 13KB
trainpso.m 11KB
ga.m 11KB
tutorial_ClassRF.m 10KB
psooptimset.m 10KB
get_psoOptions.m 10KB
tutorial_RegRF.m 9KB
goplotpso4net.m 8KB
pso.m 7KB
RunExp.m 7KB
migrate.m 7KB
dists.m 7KB
gademo3.m 6KB
SVR.m 6KB
goplotpso.m 6KB
psoSVMcgForClass.m 6KB
reins.m 5KB
mapminmax_new.m 5KB
psoSVMcgForRegress.m 5KB
plotroc.m 5KB
psocheckinitialpopulation.m 5KB
mutbga.m 5KB
goplotpso4demo.m 5KB
DemoPSOBehavior.m 5KB
recmut.m 5KB
Contents.m 5KB
psocheckbounds.m 5KB
ranking.m 5KB
normmat.m 4KB
main.m 4KB
SVC.m 4KB
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