Local relation mapping theory of fuzzy reasoning

Author

Pan, Wuming ; Tang, Yongchuan ; Xu, Yang ; Qin, Kexun

Author_Institution

Dept. of Appl. Math., Southwest Jiaotong Univ., Sichuan, China

Volume

4

fYear

2001

fDate

2001

Firstpage

2145

Abstract

Many authors discussed the interpolation mechanism of fuzzy logic system applied in control. The input and output of fuzzy control system are always restrained in (fuzzy) numbers-associated with fuzzification and defuzzification procedure. In artificial intelligence area we need use common fuzzy sets to represent vague and fuzzy concept. In this paper, we propose a "local relation mapping" theory, which is a corresponding result of interpolation mechanism of fuzzy logical system without fuzzification and defuzzification. This local relation mapping property holds in Mamdani algorithm (Max-Min fuzzy reasoning model). We find that each CRI fuzzy reasoning method based on the multi-valued logic implication operator has an approximate Mamdani algorithm. The fuzzy relation matrix of CRI fuzzy inference method based on the multivalued logic implication operator has an enveloping surface of Mamdani algorithm. So most CRI fuzzy reasoning methods have local relation mapping property approximately

Keywords

fuzzy logic; inference mechanisms; multivalued logic; CRI fuzzy inference method; Mamdani algorithm; approximate Mamdani algorithm; artificial intelligence; defuzzification; fuzzification; fuzzy control system; fuzzy logic system; fuzzy reasoning; local relation mapping theory; multi-valued logic; Artificial intelligence; Control systems; Fuzzy control; Fuzzy logic; Fuzzy reasoning; Fuzzy sets; Fuzzy systems; Inference algorithms; Interpolation; Multivalued logic;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 2001 IEEE International Conference on

Conference_Location

Tucson, AZ

ISSN

1062-922X

Print_ISBN

0-7803-7087-2

Type

conf

DOI

10.1109/ICSMC.2001.972873

Filename

972873