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Karim Faez
Amirkabir University of Tech
Computer Science & IT Electrical & Electronics Engineering

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Adaptive Adjustment of PSO Coefficients Taking the Notion from the Bee Behavior in Collecting Nectar Abbas Fadavi; Karim Faez; Zeinab Famili
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 5: October 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (261.072 KB) | DOI: 10.11591/ijece.v6i5.pp2470-2477

Abstract

In particle swarm optimization, a set of particles move towards the global optimum point according to their experience and experience of other particles. Parameters such as particle rate, particle best experience, the best experience of all the particles and particle current position are used to determine the next position of each particle. Certain relationships received the input parameters and determined the next position of each particle. In this article, the relationships are accurately assessed and the amount of the effect of input parameters is horizontally set. To set coefficients adaptively, the notion is taken from bee behavior in collecting nectar. This method was implemented on software and examined in the standard search environments. The obtained results indicate the efficiency of this method in increasing the rate of convergence of particles towards the global optimum.
Co-Authors Abbas Fadavi Zeinab Famili