A new indirect approach to the type-2 fuzzy systems modeling and design

• Published in: Information sciences Vol. 232; pp. 346 - 365
• Main Authors: Fazel Zarandi, M.H., Doostparast Torshizi, A., Turksen, I.B., Rezaee, B.
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 20.05.2013
• Subjects: Cluster validity index; Type-2 fuzzy logic system; Uncertainty bound; Type-2 fuzzy logic system; Cluster validity index; Uncertainty bound
• ISSN: 0020-0255; 1872-6291
• DOI: 10.1016/j.ins.2012.12.017

This paper proposes a new method for designing Interval Type-2 Fuzzy Logic Systems (IT2 FLSs) considering two issues: first, quality of clustering the output space and secondly, approximating the output of the IT2 FLS based on a new output processing method. Based on these two issues, we present a new cluster validity index capable of being used for type-1 Fuzzy C-Means (FCMs), Interval Type-2 FCM (IT2 FCM), and Possibilistic C-Means (PCMs) clustering algorithms. This validity index is highly efficient in determining clusters with the least similarity between them and the highest similarity between data vectors in each cluster. Then, a new definition for uncertainty bounds is presented in order to eliminate the type-reduction process in IT2 FLSs and to increase accuracy of the existing uncertainty bounds in the literature. Finally, effectiveness of the proposed approaches compared to several well-known existing methods has been investigated. Computational results have verified accuracy and effectiveness of the proposed method.