Artificial bee colony and particle swarm optimization for the estimation of nonlinear regression parameters

This paper shows the comparison results of ABC (Artificial Bee Colony) and PSO (Particle Swarm Optimization) heuristic tech- niques that were used to estimate parameters for nonlinear regression models. The algorithms were tested on 27 data bases from the NIST collection (2001), 8 of these are consi...

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Main Authors: de los Cobos Silva, Sergio Gerardo, Gutiérrez Andrade, Miguel Ángel, Rincón García, Eric Alfredo, Lara Velázquez, Pedro, Aguilar Cornejo, Manuel
Format: Artículo
Language: Español
Published: 2015
Subjects:
Online Access: http://revistas.ucr.ac.cr/index.php/matematica/article/view/14141
http://hdl.handle.net/10669/13048
Summary: This paper shows the comparison results of ABC (Artificial Bee Colony) and PSO (Particle Swarm Optimization) heuristic tech- niques that were used to estimate parameters for nonlinear regression models. The algorithms were tested on 27 data bases from the NIST collection (2001), 8 of these are considered to have high difficulty, 11 medium difficulty and 8 low difficulty. Experimental results are presented.