Neural Computing and Applications, ( ISI ), Volume (21), No (21), Year (2012-4) , Pages (29-41)

Title : ( Model-based fuzzy c-shells clustering )

Authors: Hadi Sadoghi Yazdi , hadi mahdipour , Morteza Khademi ,

Citation: BibTeX | EndNote

In this paper, a new shell clustering method is presented to cluster model-based shells in 2-dimensions. Shells, that each one of them can be expressed by a center and non-negative radius in each angle (by considering polar coordinate system), can cluster by using the proposed model-based fuzzy c-shells (MFCS) clustering method. In this paper, firstly one of the most famous traditionally clustering methods, i.e. fuzzy c-spherical shells (FCSS) clustering method, is extracted from the proposed MFCS clustering method as a specific state of it. Then, the per- formance of proposed method is examined in three exam- ples when it is applied over shells with various shapes in 2-dimensions. Since the resulted systems of equations in the studied examples cannot be solved directly, the particle swarm optimization (PSO) algorithm is used to numeri- cally solve the resulted equations systems. The simulation results show the acceptable performance of the proposed MFCS method.

Keywords

, Model, based fuzzy c, shells (MFCS) Fuzzy c, spherical shell (FCSS)
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@article{paperid:1022796,
author = {Sadoghi Yazdi, Hadi and Mahdipour, Hadi and Khademi, Morteza},
title = {Model-based fuzzy c-shells clustering},
journal = {Neural Computing and Applications},
year = {2012},
volume = {21},
number = {21},
month = {April},
issn = {0941-0643},
pages = {29--41},
numpages = {12},
keywords = {Model-based fuzzy c-shells (MFCS) Fuzzy c-spherical shell (FCSS) Clustering},
}

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%0 Journal Article
%T Model-based fuzzy c-shells clustering
%A Sadoghi Yazdi, Hadi
%A Mahdipour, Hadi
%A Khademi, Morteza
%J Neural Computing and Applications
%@ 0941-0643
%D 2012

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