IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

On Combining Nature-Inspired Algorithms for Data Clustering

On Combining Nature-Inspired Algorithms for Data Clustering
View Sample PDF
Author(s): Hanan Ahmed (Ain Shams University, Egypt), Howida A. Shedeed (Ain Shams University, Egypt), Safwat Hamad (Ain Shams University, Egypt) and Mohamed F. Tolba (Ain Shams University, Egypt)
Copyright: 2017
Pages: 30
Source title: Handbook of Research on Machine Learning Innovations and Trends
Source Author(s)/Editor(s): Aboul Ella Hassanien (Cairo University, Egypt) and Tarek Gaber (Suez Canal University, Egypt)
DOI: 10.4018/978-1-5225-2229-4.ch036

Purchase

View On Combining Nature-Inspired Algorithms for Data Clustering on the publisher's website for pricing and purchasing information.

Abstract

This chapter proposed different hybrid clustering methods based on combining particle swarm optimization (PSO), gravitational search algorithm (GSA) and free parameters central force optimization (CFO) with each other and with the k-means algorithm. The proposed methods were applied on 5 real datasets from the university of California, Irvine (UCI) machine learning repository. Comparative analysis was done in terms of three measures; the sum of intra cluster distances, the running time and the distances between the clusters centroids. The initial population for the used algorithms were enhanced to minimize the sum of intra cluster distances. Experimental results show that, increasing the number of iterations doesn't have a noticeable impact on the sum of intra cluster distances while it has a negative impact on the running time. K-means combined with GSA (KM-GSA), PSO combined with GSA (PSO-GSA) gave the best performance according to the sum of intra cluster distances while K-means combined with PSO (KM-PSO) and KM-GSA were the best in terms of the running time. Finally, KM-GSA and GSA have the best performance.

Related Content

Junichiro Hayano, Emi Yuda. © 2021. 15 pages.
Anna Karagianni, Vasiliki Geropanta, Panagiotis Parthenios, Riccardo Porreca, Sofia Mavroudi, Antonios Vogiatzis, Lais-Ioanna Margiori, Christos Mpaknis, Eleutheria Papadosifou, Asimina Ioanna Sampani. © 2021. 21 pages.
Elias Munapo. © 2021. 16 pages.
Elias Munapo, Olusegun Sunday Ewemooje. © 2021. 16 pages.
Zakhid Godzhaev, Sergey Senkevich, Viktor Kuzmin, Izzet Melikov. © 2021. 19 pages.
Elias Munapo. © 2021. 22 pages.
Diriba Kajela Geleta, Mukhdeep Singh Manshahia. © 2021. 39 pages.
Body Bottom