Finding Best Clustering For Big Networks with Minimum Objective Function by Using Probabilistic Tabu Search

  • Ali Falah Yaqoob Department of Computer Science, College of Science, University of Baghdad, Baghdad, Iraq
  • Basad Al-Sarray Department of Computer Science, College of Science, University of Baghdad, Baghdad, Iraq

Abstract

     Fuzzy C-means (FCM) is a clustering method used for collecting similar data elements within the group according to specific measurements. Tabu is a heuristic algorithm. In this paper, Probabilistic Tabu Search for FCM implemented to find a global clustering based on the minimum value of the Fuzzy objective function. The experiments designed for different networks, and cluster’s number the results show the best performance based on the comparison that is done between the values of the objective function in the case of using standard FCM and Tabu-FCM, for the average of ten runs.

Published
Aug 26, 2019
How to Cite
YAQOOB, Ali Falah; AL-SARRAY, Basad. Finding Best Clustering For Big Networks with Minimum Objective Function by Using Probabilistic Tabu Search. Iraqi Journal of Science, [S.l.], p. 1837-1845, aug. 2019. ISSN 2312-1637. Available at: <http://scbaghdad.edu.iq/eijs/index.php/eijs/article/view/1024>. Date accessed: 17 sep. 2019.
Section
Computer Science