Fuzzy dynamic turning for particle swarm optimization with weighted particle

Nai Jen Li, Wen June Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

This study proposes a fuzzy dynamic turning (FDT) strategy to adjust inertia weight of the enhanced particle swarm optimization incorporating a weighted particle (EPSOWP). In the proposed study, EPSOWP has two principal updating search behaviors which are switched alternately. One of the two behaviors includes the term w×v(t) where w is the inertia weight and v(t) is the velocity. The term w×v(t) gives a search direction based on the particle flying velocity of the last generation. Moreover, a good inertia weight could provide an excellent search direction. Therefore, we use fuzzy reasoning technique to turn the inertia weight of EPSOWP dynamically. The simulation results show that the proposed EPSOWP has outstanding performance on benchmark functions.

Original languageEnglish
Title of host publication11th IEEE International Conference on Control and Automation, IEEE ICCA 2014
PublisherIEEE Computer Society
Pages208-212
Number of pages5
ISBN (Print)9781479928378
DOIs
StatePublished - 2014
Event11th IEEE International Conference on Control and Automation, IEEE ICCA 2014 - Taichung, Taiwan
Duration: 18 Jun 201420 Jun 2014

Publication series

NameIEEE International Conference on Control and Automation, ICCA
ISSN (Print)1948-3449
ISSN (Electronic)1948-3457

Conference

Conference11th IEEE International Conference on Control and Automation, IEEE ICCA 2014
Country/TerritoryTaiwan
CityTaichung
Period18/06/1420/06/14

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