Título: Incorporação de Recorrência em Estruturas Neurofuzzy
Autores: Luna, Ivette; Ballini, Rosangela; Gomide, Fernando
Resumo: Hybrid neurofuzzy networks are addressed in this paper. The network models have two basicstructures, a fuzzy neural inference system and a neural network. The fuzzy system contains fuzzy neurons modeled through logic ”and” and ”or” operations processed via t-norms and s-norms, respectively.The neural fuzzy inference. Learning is based on an associative reinforcement learning to update second layer weights. The recurrent fuzzy neural network is particularly suitable to model nonlinear dynamic processes. Computational experiments with modeling of an unknown nonlinear process suggest that the hybrid fuzzy neural models are simpler, learning is faster, and that approximation errors are lower when compared with its counterparts.
Palavras-chave:
Páginas: 6
Código DOI: 10.21528/CBRN2003-024
Artigo em PDF: 6CBRN_024.PDF
Arquivo BibTex: 6CBRN_024.bib