Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/96017
Type: Artigo de evento
Title: Genetic-neuro-fuzzy Systems: A Promising Fusion
Author: Nobre Farley Simon M.
Abstract: The aim of this paper is to emphasize some advantages of the fusion of artificial intelligence techniques such as fuzzy logic, neural nets and genetic algorithms. The design of neurofuzzy nets based on AND-OR logical neurons are discussed. Afterward, some ways for designing and automatic tuning of fuzzy system parameters using genetic algorithms are described. In the end, methods to provide parametric and structural learning of neural nets using genetic algorithms are presented and from these concepts the definition of Regenerative Neural Nets is introduced.
Editor: IEEE, Piscataway, NJ, United States
Rights: fechado
Identifier DOI: 
Address: http://www.scopus.com/inward/record.url?eid=2-s2.0-0029213704&partnerID=40&md5=c992ff0b33bf75a0f5362b41c1103dc1
Date Issue: 1995
Appears in Collections:Unicamp - Artigos e Outros Documentos

Files in This Item:
File Description SizeFormat 
2-s2.0-0029213704.pdf480.65 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.