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148607

INTELLIGENT CLUSTERING TECHNIQUE BASED ON GENETIC ALGORITHM

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Last updated: 22 Jan 2023

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Abstract

This paper focuses on the problems of data clustering where the similarity between different objects is estimated with the use of the Euclidean distance metric. Also, K-Means is used to remove data noise, genetic algorithms are used for finding the optimal set of features and the Support Vector, Machine (SVM) is used as a classifier. The experimental results prove that the proposed model has attained an accuracy of 94.79 % when using three datasets taken from the UCI repository.

DOI

10.21608/ijicis.2021.148607

Keywords

Data mining, Clustering, Genetic Algorithms, Feature Extraction, K-means

Authors

First Name

shaymaa

Last Name

abdulrahman

MiddleName

-

Affiliation

ain shams university

Email

shaymaaa416@gmail.com

City

-

Orcid

-

First Name

Mohamed

Last Name

Roushdy

MiddleName

Ismail

Affiliation

Faculty of Computer and Information Technology, Future University in Egypt, Cairo, Egypt

Email

mohamed.roushdy@fue.edu.eg

City

Cairo

Orcid

0000-0002-9655-3229

First Name

Abdel-Badeeh

Last Name

Salem

MiddleName

M.

Affiliation

Computer Sciece Department, Faculty of Computer and Information Sciences, Ain Shams University

Email

absalem@cis.asu.edu.eg

City

-

Orcid

0000-0001-5013-4339

Volume

21

Article Issue

1

Related Issue

21725

Issue Date

2021-02-01

Receive Date

2021-01-12

Publish Date

2021-02-01

Page Start

19

Page End

32

Print ISSN

1687-109X

Online ISSN

2535-1710

Article File

IJICIS_Volume 21_Issue 1_Pages 19-32.pdf

PDF . 762.5kB

Link

https://ijicis.journals.ekb.eg/article_148607.html

Detail API

https://ijicis.journals.ekb.eg/service?article_code=148607

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Type

Original Article

Type Code

494

Publication Type

Journal

Publication Title

International Journal of Intelligent Computing and Information Sciences

Publication Link

https://ijicis.journals.ekb.eg/

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Article

Created At

22 Jan 2023