Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/75897
Type: Artigo de periódico
Title: A HIGH-LEVEL NET APPROACH FOR DISCOVERING POTENTIAL INCONSISTENCIES IN FUZZY KNOWLEDGE BASES
Author: SCARPELLI, H
GOMIDE, F
Abstract: The problem of verifying the integrity of fuzzy knowledge bases is discussed. An approach to find potential inconsistencies in fuzzy rule based systems is described. The approach models the knowledge base as a High Level Fuzzy Petri Net and uses the structural properties of the net for verification. Basic notions on approximate reasoning, regular and hierarchical High Level Fuzzy Petri Nets are also given. The method used for consistency checking is reviewed through the analysis of several cases including simple and chaining rules. Procedures for discovering potential inconsistencies at both local and global levels are described.
Subject: APPROXIMATE REASONING
ARTIFICIAL INTELLIGENCE
INFORMATION PROCESSING
GRAPH PROBLEMS
ENGINEERING
Country: Holanda
Editor: Elsevier Science Bv
Rights: fechado
Identifier DOI: 10.1016/0165-0114(94)90332-8
Date Issue: 1994
Appears in Collections:Unicamp - Artigos e Outros Documentos

Files in This Item:
File Description SizeFormat 
WOSA1994NZ36700004.pdf1.06 MBAdobe PDFView/Open


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