DocumentCode
2445447
Title
Stereotyping: improving particle swarm performance with cluster analysis
Author
Kennedy, James
Author_Institution
Bur. of Labor Stat., Washington, DC, USA
Volume
2
fYear
2000
fDate
2000
Firstpage
1507
Abstract
Individuals in the particle swarm population were “stereotyped” by cluster analysis of their previous best positions. The cluster centers then were substituted for the individuals´ and neighbors´ best previous positions in the algorithm. The experiments, which were inspired by the social-psychological metaphor of social stereotyping, found that performance could be generally improved by substituting individuals´, but not neighbors´, cluster centers for their previous bests
Keywords
pattern recognition; stereo image processing; cluster analysis; particle swarm performance; social-psychological metaphor; stereotyping; Acceleration; Clustering algorithms; Collaboration; Humans; Optimization methods; Particle swarm optimization; Performance analysis; Prototypes; Psychology; Statistical analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2000. Proceedings of the 2000 Congress on
Conference_Location
La Jolla, CA
Print_ISBN
0-7803-6375-2
Type
conf
DOI
10.1109/CEC.2000.870832
Filename
870832
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