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

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Библиографические подробности
Авторы:	De-Los-Cobos-Silva, Sergio, Gutiérrez-Andrade, Miguel A., Rincón-García, Eric A., Lara-Velázquez, Pedro, Aguilar-Cornejo, Manuel
Формат:	artículo original
Статус:	Versión publicada
Дата публикации:	2014
Описание:	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.
Страна:	Portal de Revistas UCR
Институт:	Universidad de Costa Rica
Repositorio:	Portal de Revistas UCR
Язык:	Español
OAI Identifier:	oai:archivo.portal.ucr.ac.cr:article/14141
Online-ссылка:	https://archivo.revistas.ucr.ac.cr/index.php/matematica/article/view/14141
Ключевое слово:	artificial bee colony particle swarm optimization nonlinear regression colonias de abejas artificiales enjambres de partículas regresión no lineal