A fuzzy C-means type clustering algorithm on triangular fuzzy numbers

Authors:
Rong Lan;Jiu-lun Fan
Affiliations:
Department of Information and Control, Xi'an Institute of Post and Telecommunications, Xi'an, China and School of Electronic Engineering, Xidian University, Xi'an, China;Department of Information and Control, Xi'an Institute of Post and Telecommunications, Xi'an, China
Venue:
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 3
Year:
2009

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Abstract

Fuzzy number type data is a typical class of fuzzy data, and it can be regarded as a general form of the interval data and the crisp data. This paper studies fuzzy clustering algorithm for triangular fuzzy numbers. First of all, we give a novel distance between triangular fuzzy numbers by using three parameters interval number, and prove that the proposed distance is a complete metric on the set of triangular fuzzy numbers. And then, based on this novel distance, we propose two fuzzy c-means type clustering algorithms for dealing with triangular fuzzy numbers. Finally, some numerical examples are provided to illustrate the algorithm's effectiveness.