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First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008)
A Multi-Subpopulation Accelerating Particle Swarm Optimization
Adelaide, Australia
January 23-January 24
ISBN: 0-7695-3090-7
ASCII Text
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Yi Jiang, "A Multi-Subpopulation Accelerating Particle Swarm Optimization," International Workshop on Knowledge Discovery and Data Mining, pp. 379-382, First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008), 2008.
 
 
BibTex
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@article{ 10.1109/WKDD.2008.69,
author = {Yi Jiang},
title = {A Multi-Subpopulation Accelerating Particle Swarm Optimization},
journal ={International Workshop on Knowledge Discovery and Data Mining},
volume = {0},
year = {2008},
isbn = {0-7695-3090-7},
pages = {379-382},
doi = {http://doi.ieeecomputersociety.org/10.1109/WKDD.2008.69},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - International Workshop on Knowledge Discovery and Data Mining
TI - A Multi-Subpopulation Accelerating Particle Swarm Optimization
SN - 0-7695-3090-7
SP379
EP382
A1 - Yi Jiang,
PY - 2008
VL - 0
JA - International Workshop on Knowledge Discovery and Data Mining
ER -
 
The particle swarm optimization is a stochastic, population-based optimization technique that can be applied to a wide range of problems. A multisubpopulation accelerating particle swarm optimization(MAPSO)is proposed to improve the performance of the original algorithm. MAPSO views the excellent individuals as attractors and generates local small populations in the neighbor of them to maintain the diversity of the population. In the course of searching, MAPSO constantly shrinks the searching neighbor and uses the accelerating operators to speed up the evolution of MAPSO. Finally, MAPSO's efficiency is validated through optimization of benchmark functions.
Citation:
Yi Jiang, "A Multi-Subpopulation Accelerating Particle Swarm Optimization," wkdd, pp.379-382, First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008), 2008
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