Finding best clustering for big networks with minimum objective function by using probabilistic Tabu search
Other Title(s)
إيجاد أفضل تعنقد للشبكات الكبيرة باستخدام طريقة تابو الاحتمالية البحثية
Joint Authors
Yaqub, Ali Falah
al-Saray, Basad Ali
Source
Issue
Vol. 60, Issue 8 (31 Aug. 2019), pp.1837-1845, 9 p.
Publisher
University of Baghdad College of Science
Publication Date
2019-08-31
Country of Publication
Iraq
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Topics
Abstract EN
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.
American Psychological Association (APA)
Yaqub, Ali Falah& al-Saray, Basad Ali. 2019. Finding best clustering for big networks with minimum objective function by using probabilistic Tabu search. Iraqi Journal of Science،Vol. 60, no. 8, pp.1837-1845.
https://search.emarefa.net/detail/BIM-969464
Modern Language Association (MLA)
Yaqub, Ali Falah& al-Saray, Basad Ali. Finding best clustering for big networks with minimum objective function by using probabilistic Tabu search. Iraqi Journal of Science Vol. 60, no. 8 (2019), pp.1837-1845.
https://search.emarefa.net/detail/BIM-969464
American Medical Association (AMA)
Yaqub, Ali Falah& al-Saray, Basad Ali. Finding best clustering for big networks with minimum objective function by using probabilistic Tabu search. Iraqi Journal of Science. 2019. Vol. 60, no. 8, pp.1837-1845.
https://search.emarefa.net/detail/BIM-969464
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 1845
Record ID
BIM-969464