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Shuyue Wu



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Shuyue Wu


WSEAS Transactions on Systems and Control


Print ISSN: 1991-8763
E-ISSN: 2224-2856

Volume 13, 2018

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of WSEAS Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.


Volume 13, 2018



Particle Swarm Optimization Research Base on Quantum Self Learning Behavior

AUTHORS: Shuyue Wu

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ABSTRACT: Particle swarm optimization algorithm is analyzed base on quantum behaved self learning, particles searching action and local attract point are studied. To the different searching environment in searching progress, the searching actions are divided into four models. The proposed algorithm can self learn the optimization problem, and utilize a suitable learning model, then the whole optimization performance is increased. The comparison and analysis of results with the proposed method and other improved QPSO are given based on CEC2005 benchmark function, the simulation results show the modified algorithm can greatly improve the QPSO performance.

KEYWORDS: Particle Swarm Optimization(PSO), quantum behavior, self learning, local attract point, searching model, evolutionary

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WSEAS Transactions on Systems and Control, ISSN / E-ISSN: 1991-8763 / 2224-2856, Volume 13, 2018, Art. #15, pp. 122-128


Copyright © 2018 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0

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