Clustering for Big Networks using Probabilistic Tabu Search
Finding Best Clustering for Big Networks with Minimum Objective Function by Using Probabilistic Tabu Search
(Sprache: Englisch)
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...
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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. We present Tabu Search for Fuzzy c-Means to estimate the best clustering by finding the best values of Fuzzy objective function and apply it on different types of real networks, the results show the ability of Tabu search to find the global solution and determine the centroids, this step is important to find the community detection of the big networks.
Autoren-Porträt von Ali Yaqoob, Basad Al-Sarray
Yaqoob, AliAli Yaqoob graduated from University of Baghdad - College of Science - Computer Science Department. He specializes in Information Technology, Programming, Software and Hardware.
Bibliographische Angaben
- Autoren: Ali Yaqoob , Basad Al-Sarray
- 2020, 160 Seiten, Maße: 22 cm, Kartoniert (TB), Englisch
- Verlag: LAP Lambert Academic Publishing
- ISBN-10: 6200459223
- ISBN-13: 9786200459220
Sprache:
Englisch
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