Please use this identifier to cite or link to this item:
http://dspace.cityu.edu.hk/handle/2031/5963
Title: | Particle Swarm Optimization |
Authors: | Wong, Yuen Lam |
Department: | Department of Electronic Engineering |
Issue Date: | 2010 |
Supervisor: | Supervisor: Dr. Wu, Angus K M; Assessor: Dr. Leung, Andrew C S |
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. |
Appears in Collections: | Electrical Engineering - Undergraduate Final Year Projects |
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