Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/15731
Title: A quantum-based particle swarm optimization algorithm applied to inverse problems
Authors: Ho, SL 
Yang, S
Ni, G
Huang, J
Issue Date: 2013
Source: IEEE transactions on magnetics, 2013, v. 49, no. 5, 6514656, p. 2069-2072
Abstract: To balance exploration and exploitation searches in order to prevent premature convergences in Particle Swarm Optimization (PSO) algorithms, an improved Quantum-based PSO (QPSO) algorithm is proposed with an ultimate goal of preserving the simplicities of available QPSOs. The improvements include the design of diversification and intensification phases, searching mechanisms and a strategy to shift away from the worst solutions. The proposed QPSO are compared to available optimizers on two case studies to showcase its merits.
Keywords: Evolutionary algorithm
Inverse problem
Optimal design
Particle swarm optimization
Publisher: Institute of Electrical and Electronics Engineers
Journal: IEEE transactions on magnetics 
ISSN: 0018-9464
EISSN: 1941-0069
DOI: 10.1109/TMAG.2013.2237760
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

21
Last Week
0
Last month
0
Citations as of Aug 28, 2020

WEB OF SCIENCETM
Citations

20
Last Week
0
Last month
0
Citations as of Sep 22, 2020

Page view(s)

159
Last Week
6
Last month
Citations as of Sep 21, 2020

Google ScholarTM

Check

Altmetric


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