Resumo

DE-LOS-COBOS-SILVA, Sergio et al. Bee colony and particle swarm optimization for the estimation of nonlinear regression parameters. Rev. Mat [online]. 2014, vol.21, n.1, pp.107-126. ISSN 1409-2433.

This paper shows the comparison results of ABC (Artificial Bee Colony) and PSO (Particle Swarm Optimization) heuristic techniques 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.

Palavras-chave : artificial bee colony; particle swarm optimization; nonlinear regression.

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