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

 

保存先:
書誌詳細
著者: De-Los-Cobos-Silva, Sergio, Gutiérrez-Andrade, Miguel A., Rincón-García, Eric A., Lara-Velázquez, Pedro, Aguilar-Cornejo, Manuel
フォーマット: artículo original
状態:Versión publicada
出版日付:2014
その他の書誌記述: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.  
国:Portal de Revistas UCR
機関:Universidad de Costa Rica
Repositorio:Portal de Revistas UCR
言語:Español
OAI Identifier:oai:archivo.portal.ucr.ac.cr:article/14141
オンライン・アクセス:https://archivo.revistas.ucr.ac.cr/index.php/matematica/article/view/14141
キーワード:artificial bee colony
particle swarm optimization
nonlinear regression
colonias de abejas artificiales
enjambres de partículas
regresión no lineal