Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/53680
Type: Artigo de periódico
Title: A reasoning algorithm for high-level fuzzy petri nets
Author: Scarpelli, H
Gomide, F
Yager, RR
Abstract: In this paper, we introduce an automated procedure fur extracting information from knowledge bases that contain fuzzy production rules, The knowledge bases considerrd here are modeled using the high-level fuzzy Petri nets proposed by the authors in the past, Extensions to the high-level fuzzy Petri net model are given to include the representation of partial sources of information, The case of rules with more than one variable in the consequent is also discussed, A reasoning algorithm based on the high-level fuzzy Petri net model is presented, The algorithm consists of the extraction of a subnet and an evaluation process. In the evaluation process, several fuzzy inference methods can be applied, The proposed algorithm is similar to another procedure suggested by Yager [20], with advantages concerning the knowledge-base searching when gathering the relevant information to answer a particular kind of query.
Editor: Ieee-inst Electrical Electronics Engineers Inc
Rights: fechado
Identifier DOI: 10.1109/91.531771
Date Issue: 1996
Appears in Collections:Artigos e Materiais de Revistas Científicas - Unicamp

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