Title :
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
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;
Conference_Titel :
Fuzzy Systems Conference Proceedings, 1999. FUZZ-IEEE '99. 1999 IEEE International
Conference_Location :
Seoul, South Korea
Print_ISBN :
0-7803-5406-0
DOI :
10.1109/FUZZY.1999.790135
