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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Autores Principales: de los Cobos Silva, Sergio Gerardo, Gutiérrez Andrade, Miguel Ángel, Rincón García, Eric Alfredo, Lara Velázquez, Pedro, Aguilar Cornejo, Manuel
Formato: Artículo
Idioma: Español
Publicado: 2015
Materias:
Acceso en línea: http://revistas.ucr.ac.cr/index.php/matematica/article/view/14141
http://hdl.handle.net/10669/13048
Sumario: 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.