MBA-LF: A NEW DATA CLUSTERING METHOD USING MODIFIED BAT ALGORITHM AND LEVY FLIGHT
Data clustering plays an important role in partitioning the large set of data objects into known/unknown number of groups or clusters so that the objects in each cluster are having high degree of similarity while objects in different clusters are dissimilar to each other. Recently a number of data c...
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Veröffentlicht in: | ICTACT journal on soft computing 2015-10, Vol.6 (1), p.1093-1101 |
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Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
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Online-Zugang: | Volltext |
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Zusammenfassung: | Data clustering plays an important role in partitioning the large set of data objects into known/unknown number of groups or clusters so that the objects in each cluster are having high degree of similarity while objects in different clusters are dissimilar to each other. Recently a number of data clustering methods are explored by using traditional methods as well as nature inspired swarm intelligence algorithms. In this paper, a new data clustering method using modified bat algorithm is presented. The experimental results show that the proposed algorithm is suitable for data clustering in an efficient and robust way. |
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ISSN: | 0976-6561 2229-6956 |
DOI: | 10.21917/ijsc.2015.0151 |