Busca avançada
Ano de início
Entree


Nullneurons-based hybrid neurofuzzy network

Texto completo
Autor(es):
Hell, Michel ; Costa, Pyramo, Jr. ; Gomide, Fernando ; Reformat, M ; Berthold, MR
Número total de Autores: 5
Tipo de documento: Artigo Científico
Fonte: NAFIPS 2007 - 2007 ANNUAL MEETING OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY; v. N/A, p. 2-pg., 2007-01-01.
Resumo

In this paper we introduce design and learning schemes for hybrid neurofuzzy networks based on nullneurons. A nullneuron is a logic neuron that performs an operation Psi parameterized by u (absorbing element). The nullneuron becomes a AND neuron if u = 0 and a dual OR neuron if u = 1. The operator Psi is a composition of nullnorms. Based on input-output data, the learning procedure proposed here adjusts not only the weights associated with the individual inputs of the nullneurons, but also the type of the nullneuron in the network (AND or OR) learning the value of parameter u. Adjustment of u is done individually and after learning each nullneuron can be either a AND neuron or a OR neuron, independently of the state of the remaining nullneurons. Consequently, the neurofuzzy network presented in this paper is more general than alternative approaches discussed in the literature because it embeds a set of if-then rules that uses different connectives in their antecedents. Experimental results are included to show that the neurofuzzy network proposed provides accurate models after short period of learning time. (AU)

Processo FAPESP: 03/10019-9 - Metodologias de previsão para sistemas de energia
Beneficiário:Fernando Antonio Campos Gomide
Modalidade de apoio: Auxílio à Pesquisa - Temático
Processo FAPESP: 03/05042-1 - Abordagem neurofuzzy para modelagem de sistemas dinamicos nao lineares.
Beneficiário:Michel Bortolini Hell
Modalidade de apoio: Bolsas no Brasil - Doutorado