Title : ( Fuzzy clustering Algorithm for fuzzy data based on alpha-cuts )
Authors: Sohrab Effati ,
Full TextAbstract
This paper presents fuzzy clustering algorithm for fuzzy data based on alpha-cuts. A new suitable definition for distance between two arbitrary fuzzy numbers based on alpha-cuts is proposed. We then reformulate fuzzy c-means (FCM) with fuzzy data and fuzzy centers based on alpha-cuts. The effectiveness of the proposed clustering algorithm is tested for two fuzzy data sets and then it is compared with two other methods; the fuzzy c-number (FCN) algorithm and the mixed-type variables FCM (MVFCM) algorithm.
Keywords
, alpha, cut; Fuzzy numbers; Fuzzy c, means; Fuzzy clustering; Fuzzy data; Dissimilarity measure.
@inproceedings{paperid:1009471,
author = {Effati, Sohrab},
title = {Fuzzy clustering Algorithm for fuzzy data based on alpha-cuts},
booktitle = {Second Joint Congress on Fuzzy & Inelligent Systems},
year = {2008},
location = {IRAN},
keywords = {alpha-cut; Fuzzy numbers; Fuzzy c-means; Fuzzy
clustering; Fuzzy data; Dissimilarity measure.},
}
%0 Conference Proceedings
%T Fuzzy clustering Algorithm for fuzzy data based on alpha-cuts
%A Effati, Sohrab
%J Second Joint Congress on Fuzzy & Inelligent Systems
%D 2008
