ISJ Theoretical & Applied Science 07(27) 2015

ISPC Intelligent technologies, Marseille, France

Matrenin PV, Sekaev VG

DATA MINING FOR PARAMETER SELECTION OF SWARM INTELLIGENCE ALGORITHMS.

Full Article: PDF

Scientific Object Identifier: http://s-o-i.org/1.1/TAS-07(27)13

DOI: http://dx.doi.org/10.15863/TAS.2015.07.27.13

Language: Russian

Citation: Matrenin PV, Sekaev VG (2015) DATA MINING FOR PARAMETER SELECTION OF SWARM INTELLIGENCE ALGORITHMS. ISJ Theoretical & Applied Science 07 (27): 75-81. Soi: http://s-o-i.org/1.1/TAS-07-27-13 Doi: http://dx.doi.org/10.15863/TAS.2015.07.27.13

Pages: 75-81

Published: 30.07.2015

Abstract: Swarm Intelligence algorithms commonly used to solve optimization problems. This study considers the problem of the parameters selection of the Particle Swarm Optimization algorithm. Methods of data mining are proposed to use for the selection. An example of applying regression analysis and classifying for Particle Swarm Optimization are given. The analysis carried out allows us to find good parameters of the Particle Swarm Optimization algorithm for a test optimization problem. The effectiveness of parameters found has been compared with parameters recommended by other researchers.

Key words: adaptation, data mining, particle swarm optimization, parameters selection, regression, analysis.