Date of Award
Spring 5-2017
Degree Type
Thesis
Degree Name
M.S.
Degree Program
Electrical Engineering
Department
Electrical Engineering
Major Professor
Dr. Dimitrios Charalampidis
Abstract
This thesis discusses clustering related works with emphasis on Particle Swarm Optimization (PSO) principles. Specifically, we review in detail the PSO clustering algorithm proposed by Van Der Merwe & Engelbrecht, the particle swarm clustering (PSC) algorithm proposed by Cohen & de Castro, Szabo’s modified PSC (mPSC), and Georgieva & Engelbrecht’s Cooperative-Multi-Population PSO (CMPSO). In this thesis, an improvement over Van Der Merwe & Engelbrecht’s PSO clustering has been proposed and tested for standard datasets. The improvements observed in those experiments vary from slight to moderate, both in terms of minimizing the cost function, and in terms of run time.
Recommended Citation
Shahadat, Sharif, "Improving a Particle Swarm Optimization-based Clustering Method" (2017). University of New Orleans Theses and Dissertations. 2357.
https://scholarworks.uno.edu/td/2357
Rights
The University of New Orleans and its agents retain the non-exclusive license to archive and make accessible this dissertation or thesis in whole or in part in all forms of media, now or hereafter known. The author retains all other ownership rights to the copyright of the thesis or dissertation.