An adaptive type-2 fuzzy system for learning linguistic membership grades

Author

John, R.I. ; Czarnecki, C.

Author_Institution

Fac. of Comput. Sci. & Eng., De Montfort Univ., Leicester, UK

Volume

3

fYear

1999

fDate

22-25 Aug. 1999

Firstpage

1552

Abstract

Type-2 fuzzy sets allow for linguistic grades of membership. A type-2 fuzzy inferencing systems uses type-2 fuzzy sets to represent uncertainty in both the representation and inferencing. However, as with type-1 fuzzy systems there is still an issue with regard to the design of the appropriate membership functions. This paper presents a novel type-2 adaptive system for learning the membership grades of type-2 fuzzy sets. The paper reports on some results obtained from a type-2 system developed for car evaluation. The results lead us to believe that this approach offers the capability to allow linguistic descriptors to be learnt by an adaptive network.

Keywords

adaptive systems; fuzzy set theory; fuzzy systems; inference mechanisms; learning (artificial intelligence); uncertainty handling; adaptive system; fuzzy inferencing systems; fuzzy set theory; learning; linguistic membership grades; type-2 fuzzy system; uncertainty handling; Adaptive systems; Artificial neural networks; Computational intelligence; Fuzzy logic; Fuzzy sets; Fuzzy systems; Marine vehicles; Neural networks; Temperature measurement; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems Conference Proceedings, 1999. FUZZ-IEEE '99. 1999 IEEE International

Conference_Location

Seoul, South Korea

ISSN

1098-7584

Print_ISBN

0-7803-5406-0

Type

conf

DOI

10.1109/FUZZY.1999.790135

Filename

790135