Artificial bee colony and particle swarm optimization for the estimation of nonlinear regression parameters
Guardado en:
| Autores: | , , , , |
|---|---|
| Formato: | artículo original |
| Estado: | Versión publicada |
| Fecha de Publicación: | 2014 |
| Descripción: | 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. |
| País: | Portal de Revistas UCR |
| Institución: | Universidad de Costa Rica |
| Repositorio: | Portal de Revistas UCR |
| Lenguaje: | Español |
| OAI Identifier: | oai:portal.ucr.ac.cr:article/14141 |
| Acceso en línea: | https://revistas.ucr.ac.cr/index.php/matematica/article/view/14141 |
| Access Level: | acceso abierto |
| Palabra clave: | artificial bee colony particle swarm optimization nonlinear regression colonias de abejas artificiales enjambres de partículas regresión no lineal |