Inference and improper knowledge detection on fuzzy rules with enhanced high-level fuzzy Petri nets

Author

Yang, Hsin-Tai ; Lee, Shie-Jue

Author_Institution

Dept. of Electr. Eng., Nat. Sun Yat-Sen Univ., Kaohsiung, Taiwan

fYear

1998

fDate

20-21 Aug 1998

Firstpage

135

Lastpage

139

Abstract

We propose a new version of Petri nets, enhanced high-level fuzzy Petri nets (EHLFPN), to represent fuzzy rules in knowledge bases. In the proposed model, fuzzy inference can be performed using a method similar to (Scarpelli et al., 1996). In addition, improper knowledge such as conflicts, redundancy, cycles, unnecessary conditions, dead ends, and unreachable goals, can be detected by first transforming fuzzy Petri nets into non-fuzzy Petri nets and then transforming the derived Petri nets into the reachability problems. At last, each type of improper knowledge is detected by solving a set of equations formulated from the corresponding reachability problem

Keywords

Petri nets; fuzzy logic; inference mechanisms; knowledge based systems; knowledge representation; uncertainty handling; fuzzy inference; fuzzy rules; high-level fuzzy Petri nets; improper knowledge detection; inference; knowledge bases; reachability problem; redundancy; Councils; Electronic mail; Equations; Expert systems; Fuzzy neural networks; Hybrid intelligent systems; Knowledge based systems; Logic; Mathematical model; Petri nets;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Information Processing Society - NAFIPS, 1998 Conference of the North American

Conference_Location

Pensacola Beach, FL

Print_ISBN

0-7803-4453-7

Type

conf

DOI

10.1109/NAFIPS.1998.715551

Filename

715551