A reasoning algorithm for high-level fuzzy Petri nets

Author

Scarpelli, Heloisa ; Gomide, Fernando ; Yager, Ronald R.

Author_Institution

Univ. Federal de Sao Carlos, Brazil

Volume

4

Issue

3

fYear

1996

fDate

8/1/1996 12:00:00 AM

Firstpage

282

Lastpage

294

Abstract

We introduce an automated procedure for extracting information from knowledge bases that contain fuzzy production rules. The knowledge bases considered 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 (1983), with advantages concerning the knowledge-base searching when gathering the relevant information to answer a particular kind of query

Keywords

Petri nets; fuzzy logic; fuzzy set theory; inference mechanisms; knowledge representation; evaluation process; fuzzy inference methods; fuzzy production rules; high-level fuzzy Petri nets; information extraction; knowledge bases; knowledge-base searching; reasoning algorithm; Brazil Council; Data mining; Fuzzy logic; Fuzzy reasoning; Helium; Inference algorithms; Knowledge based systems; Petri nets; Production; Tree graphs;

fLanguage

English

Journal_Title

Fuzzy Systems, IEEE Transactions on

Publisher

ieee

ISSN

1063-6706

Type

jour

DOI

10.1109/91.531771

Filename

531771