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86757

Fuzzy C-means Clustering Algorithm for Cluster Membership Determination

Article

Last updated: 25 Dec 2024

Subjects

-

Tags

ِِAdvanced Physics
Programming & computer Science
Space Engineering

Abstract

  Membership of open star clusters or Galactic open clusters is very important roles to study the formation and evaluation of gravitationally bound system. In the field of an image, the relative x and y coordinate positions of each star with respect to all the other stars are adapted. Therefore, in this paper, a new method for the determination open star cluster membership based on Fuzzy C-means Clustering algorithm is proposed. In the fuzzy clustering algorithm, a data point may belong to several clusters with different degree of memberships. Therefore, the membership values for a data point will represents the degree to which that point belongs to a particular cluster. The proposed method allows to efficiently discriminating the cluster membership from the field stars. The membership probabilities have been calculated and compared to those obtained by the other methods. To validate the method, we applied it on Berkeley 39 and NGC 188 open star clusters, where the membership stars in these clusters are obtained. The membership probability of stars clusters is assigned through the approach provides number of probable members.

DOI

10.21608/ijaebs.2020.86757

Keywords

Open clusters and associations, Individual, Fuzzy C-means clustering algorithm, Berkeley 39

Authors

First Name

I.

Last Name

Selim

MiddleName

M.

Affiliation

National Research Institute of Astronomy and Geophysics (NRIAG Dean of Thebes Institue of computer science - Cairo - Egypt.

Email

i_selim@yahoo.com

City

Cairo

Orcid

-

First Name

Mohamed

Last Name

Abd El Aziz

MiddleName

-

Affiliation

Department of Mathematics, Faculty of Science, Zagazig University, Zagazig, Egypt

Email

i.selim@thebes.edu.eg

City

-

Orcid

-

Volume

1

Article Issue

Special Issue

Related Issue

13015

Issue Date

2020-05-01

Receive Date

2020-04-03

Publish Date

2020-05-01

Page Start

1

Page End

9

Print ISSN

2682-2938

Online ISSN

2682-2946

Link

https://ijaebs.journals.ekb.eg/article_86757.html

Detail API

https://ijaebs.journals.ekb.eg/service?article_code=86757

Order

1

Type

Original Article

Type Code

1,136

Publication Type

Journal

Publication Title

International Journal of Advanced Engineering and Business Sciences

Publication Link

https://ijaebs.journals.ekb.eg/

MainTitle

Fuzzy C-means Clustering Algorithm for Cluster Membership Determination

Details

Type

Article

Created At

22 Jan 2023