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
Keywords: Evolutionary algorithm
Inverse problem
Optimal design
Particle swarm optimization
Issue Date: 2013
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on magnetics, 2013, v. 49, no. 5, 6514656, p. 2069-2072 How to cite?
Journal: IEEE transactions on magnetics 
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.
URI: http://hdl.handle.net/10397/15731
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

13
Last Week
0
Last month
0
Citations as of Aug 14, 2017

WEB OF SCIENCETM
Citations

11
Last Week
0
Last month
0
Citations as of Aug 23, 2017

Page view(s)

48
Last Week
3
Last month
Checked on Aug 20, 2017

Google ScholarTM

Check

Altmetric



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