Run Run Shaw Library
 Run Run Shaw Library

Home >
4_Student Final Year Projects >
Electronic Engineering - Undergraduate Final Year Projects >

Please use this identifier to cite or link to this item:

Title: Chaotic genetic algorithms
Authors: Yin, Jia Jia
Department: Department of Electronic Engineering
Issue Date: 2004
Supervisor: Prof. Man, K F. Assessor: Prof. Chow, Tommy W S
Abstract: The convergence properties of Genetic Algorithms are closely connected to the random sequence applied on the genetic operators during a run. As chaos and random sequence share the property of long-term unpredictable irregular behaviour and broadband spectrum, we replaced the random sequence generators by chaos generators, without affecting the original operator definitions in genetic algorithms. Three chaos models were used, the Logistic map, the Tent map and the Chua’s circuit. Both single objective functions and multi objective functions are tested in our experiments. The results show that best performance of convergence is obtained by using chaos generators.
Appears in Collections:Electronic Engineering - Undergraduate Final Year Projects

Files in This Item:

File SizeFormat
fulltext.html164 BHTMLView/Open

Items in CityU IR are protected by copyright, with all rights reserved, unless otherwise indicated.


Valid XHTML 1.0!
DSpace Software © 2013 CityU Library - Send feedback to Library Systems
Privacy Policy · Copyright · Disclaimer