Particle Swarm Optimization

Wong, Yuen Lam

Please use this identifier to cite or link to this item: http://dspace.cityu.edu.hk/handle/2031/5963

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DC Field	Value	Language
dc.contributor.author	Wong, Yuen Lam	en_US
dc.date.accessioned	2011-01-19T04:11:59Z
dc.date.accessioned	2017-09-19T09:11:42Z
dc.date.accessioned	2019-02-12T07:29:04Z	-
dc.date.available	2011-01-19T04:11:59Z
dc.date.available	2017-09-19T09:11:42Z
dc.date.available	2019-02-12T07:29:04Z	-
dc.date.issued	2010	en_US
dc.identifier.other	2010eewyl792	en_US
dc.identifier.uri	http://144.214.8.231/handle/2031/5963	-
dc.description.abstract	Particle Swarm Optimization (PSO) is a method to find the minimum of a numerical function, on a continuous definition domain. This project aims to improve the performance of PSO and further investigate that the performance of Chaotic PSO is better than PSO. The accelerator coefficients self-recognition coefficient c1 and social coefficient c2 have the great effect on the performance of PSO. The coefficient of c2 will be studied in this project. There are 5 coefficients, position of particle, fitness value of particle, linear time-varying accelerator and non-linear time-varying accelerators. 16 Benchmark test functions are used to evaluate the performance of PSO.	en_US
dc.rights	This work is protected by copyright. Reproduction or distribution of the work in any format is prohibited without written permission of the copyright owner.	en_US
dc.rights	Access is restricted to CityU users.	en_US
dc.title	Particle Swarm Optimization	en_US
dc.contributor.department	Department of Electronic Engineering	en_US
dc.description.supervisor	Supervisor: Dr. Wu, Angus K M; Assessor: Dr. Leung, Andrew C S	en_US
Appears in Collections:	Electrical Engineering - Undergraduate Final Year Projects

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