Quality and robustness improvement for real world industrial systems using a fuzzy particle swarm optimization-Reference-Cited by-同舟云学术

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Quality and robustness improvement for real world industrial systems using a fuzzy particle swarm optimization

Published:2016-01 Issue: Volume:47 Page:68-80
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Ling Sai Ho,Chan Kit Yan,Leung Frank Hung Fat,Jiang Frank,Nguyen Hung

Funder

University of Technology Sydney

Research Grants Council of the Hong Kong Special Administrative Region, China

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference40 articles.

1. A hybrid particle swarm optimization applied to loss power minimization;Ahmed;IEEE Trans. Power Syst.,2005

2. Angeline, P., 1998. Using selection to improve particle swarm optimization. In: Proceedings of the IEEE Congress on Evolutionary Computing (Anchorage), May, pp. 84–89.

3. Traffic-aware optimization of heterogeneous access management;Bühler;IEEE Trans. Commun.,2010

4. Modeling of a liquid epoxy molding process using a particle swarm optimization-based fuzzy regression approach;Chan;IEEE Trans. Ind. Inf.,2011

5. Polynomial modeling for time-varying systems based on a particle swarm optimization algorithm;Chan;Inf. Sci.,2011

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