Artificial bee colony and particle swarm optimization for the estimation of nonlinear regression parameters
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| المؤلفون: | , , , , |
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| التنسيق: | artículo original |
| الحالة: | Versión publicada |
| تاريخ النشر: | 2014 |
| الوصف: | 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. |
| البلد: | Portal de Revistas UCR |
| المؤسسة: | Universidad de Costa Rica |
| Repositorio: | Portal de Revistas UCR |
| اللغة: | Español |
| OAI Identifier: | oai:portal.ucr.ac.cr:article/14141 |
| الوصول للمادة أونلاين: | https://revistas.ucr.ac.cr/index.php/matematica/article/view/14141 |
| كلمة مفتاحية: | artificial bee colony particle swarm optimization nonlinear regression colonias de abejas artificiales enjambres de partículas regresión no lineal |