Journal of Intelligent and Fuzzy Systems, ( ISI ), Volume (26), No (2), Year (2014-1) , Pages (541-550)

Title : ( Hierarchical tree clustering of fuzzy number )

Authors: Hadi Sadoghi Yazdi , Mohammad GhasemiGol , Sohrab Effati , azam jiryani sharahi , Reza Monsefi ,

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This paper presents a new hierarchical tree approach to clustering fuzzy data, namely extensional tree (ET) clustering algorithm. It defines a dendrogram over fuzzy data and using a new distance between fuzzy numbers based on -cuts. The present work is based on hierarchical clustering algorithm unlike existing methods which improve FCM to support fuzzy data. The Proposed ET clustering algorithm is compared with some of the newly presented methods in the literature. The major advantage of ET, first tree clustering method over fuzzy number, in comparison with other algorithms is its fault tolerance against noisy samples. Some examples prove ability of the proposed ET.

Keywords

, Fuzzy data, tree clustering, dissimilarity measure,
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@article{paperid:1040536,
author = {Sadoghi Yazdi, Hadi and GhasemiGol, Mohammad and Effati, Sohrab and Jiryani Sharahi, Azam and Monsefi, Reza},
title = {Hierarchical tree clustering of fuzzy number},
journal = {Journal of Intelligent and Fuzzy Systems},
year = {2014},
volume = {26},
number = {2},
month = {January},
issn = {1064-1246},
pages = {541--550},
numpages = {9},
keywords = {Fuzzy data; tree clustering; dissimilarity measure; -cuts},
}

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%0 Journal Article
%T Hierarchical tree clustering of fuzzy number
%A Sadoghi Yazdi, Hadi
%A GhasemiGol, Mohammad
%A Effati, Sohrab
%A Jiryani Sharahi, Azam
%A Monsefi, Reza
%J Journal of Intelligent and Fuzzy Systems
%@ 1064-1246
%D 2014

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