Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569), page. 1926-1929
Abstract
This paper presents a type-2 fuzzy C-means (FCM)
algorithm that is an extension of the conventional
fuzzy C-means algorithm. In our proposed method, the
membership values for each pattern are extended as
type-2 fuzzy memberships by assigning membership
grades to the type-1 memberships. In doing so, cluster
centers that are estimated by type-2 memberships may
converge to a more desirable location than cluster
centers obtained by a type-1 FCM method in the
presence of noise. Experimental results are given to
show the effectiveness of our method.