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

Content Provider	IEEE Xplore Digital Library
Author	John, R.I. Czarnecki, C.
Copyright Year	1999
Description	Author affiliation: Fac. of Comput. Sci. & Eng., De Montfort Univ., Leicester, UK (John, R.I.)
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.
Starting Page	1552
Ending Page	1556
File Size	348655
Page Count	5
File Format	PDF
ISBN	0780354060
ISSN	10987584
DOI	10.1109/FUZZY.1999.790135
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-08-22
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Adaptive systems Fuzzy systems Fuzzy sets Artificial neural networks Temperature measurement Computational intelligence Marine vehicles Uncertainty Neural networks Fuzzy logic
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Artificial Intelligence Theoretical Computer Science Software

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