Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.1/2211
Título: Single and multi-objective genetic programming design for B-spline neural networks and neuro-fuzzy systems
Autor: Cabrita, Cristiano Lourenço
Ruano, A. E.
Fonseca, C. M.
Palavras-chave: Constructive algorithms
B-Splines
Neuro-fuzzy systems
Genetic programming
Single and multi-objective optimization
Data: 2001
Citação: Cabrita, C.; Ruano, A. E.; Fonseca, C. M. Single and Multi-Objective Genetic Programming Design for B-Spline Neural Networks and Neuro-Fuzzy Systems, Trabalho apresentado em IFAC Workshop on Advanced Fuzzy-Neural Control (AFNC' 01), In IFAC Workshop on Advanced Fuzzy-Neural Control (AFNC' 01), Valencia, 2001.
Resumo: The design phase of B-spline neural networks and neuro-fuzzy systems is a highly computationally complex task. Existent heuristics, namely the ASMOD algorithm, have been found to be highly dependent on the initial conditions employed. A Genetic Programming approach is proposed, which produces an efficient topology search, obtaining additionally more consistent solutions. The facility to incorporate a multi-objective approach to the GP algorithm is exploited, enabling the designer to obtain better conditioned models, and more adequate for their intended use.
Peer review: yes
URI: http://hdl.handle.net/10400.1/2211
Aparece nas colecções:FCT2-Artigos (em revistas ou actas indexadas)

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