Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

A Novel Chaotic Northern Bald Ibis Optimization Algorithm for Solving Different Cluster Problems [ICCICC18 #155]

A Novel Chaotic Northern Bald Ibis Optimization Algorithm for Solving Different Cluster Problems [ICCICC18 #155]
View Sample PDF
Author(s): Ravi Kumar Saidala (Acharya Nagarjuna University, Guntur, India) and Nagaraju Devarakonda (Lakireddy Bali Reddy College of Engineering, Mylavaram, India)
Copyright: 2019
Volume: 11
Issue: 2
Pages: 25
Source title: International Journal of Software Science and Computational Intelligence (IJSSCI)
Editor(s)-in-Chief: Brij Gupta (National Institute of Technology, Kurukshetra, India) and Andrew W.H. Ip (University of Saskatchewan, Canada)
DOI: 10.4018/IJSSCI.2019040101



This article proposes a new optimal data clustering method for finding optimal clusters of data by incorporating chaotic maps into the standard NOA. NOA, a newly developed optimization technique, has been shown to be efficient in generating optimal results with lowest solution cost. The incorporation of chaotic maps into metaheuristics enables algorithms to diversify the solution space into two phases: explore and exploit more. To make the NOA more efficient and avoid premature convergence, chaotic maps are incorporated in this work, termed as CNOAs. Ten different chaotic maps are incorporated individually into standard NOA for testing the optimization performance. The CNOA is first benchmarked on 23 standard functions. Secondly, testing was done on the numerical complexity of the new clustering method which utilizes CNOA, by solving 10 UCI data cluster problems and 4 web document cluster problems. The comparisons have been made with the help of obtaining statistical and graphical results. The superiority of the proposed optimal clustering algorithm is evident from the simulations and comparisons.

Related Content

Shangzhu Jin. © 2020. 14 pages.
Ravi Kumar Saidala. © 2020. 15 pages.
Carmen Campomanes-Alvarez, Blanca Rosario Campomanes-Alvarez, Pelayo Quirós. © 2020. 17 pages.
Prabir Bhattacharya, Minzhe Guo. © 2020. 21 pages.
Rachida Touami, Karima KIES, Nacéra Benamrane. © 2020. 12 pages.
Denis Pashchenko. © 2020. 14 pages.
Rinat Galiautdinov. © 2020. 19 pages.
Body Bottom