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

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.