Open AccessComputing Cluster Centers of Triangular Fuzzy Numbers using Innovative Metric Distance
Author(s) -
S. Sreenivasan*,
B. J. Balamurugan
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.j1140.0981119
Subject(s) - fuzzy number , mathematics , fuzzy set operations , fuzzy classification , fuzzy clustering , fuzzy logic , fuzzy mathematics , fuzzy set , defuzzification , cluster analysis , kernel (algebra) , metric (unit) , algorithm , discrete mathematics , computer science , artificial intelligence , statistics , operations management , economics
In this paper we compute cluster centers of triangular fuzzy numbers through fuzzy c means clustering algorithm and kernel based fuzzy c means clustering algorithm. An innovative distance between the triangular fuzzy numbers is used and the distance is complete metric on triangular fuzzy numbers. The set of triangular fuzzy numbers and an another set with the same triangular fuzzy numbers by including an outlier or noisy point as an additional triangular fuzzy number are taken to find the cluster centers using MATLAB programming. An example is given to show the effectiveness between the algorithms.