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A Dynamic Fuzzy Cluster Algorithm for Time Series
Joint Authors
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-04-16
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
This paper presents an efficient algorithm, called dynamic fuzzy cluster (DFC), for dynamically clustering time series by introducing the definition of key point and improving FCM algorithm.
The proposed algorithm works by determining those time series whose class labels are vague and further partitions them into different clusters over time.
The main advantage of this approach compared with other existing algorithms is that the property of some time series belonging to different clusters over time can be partially revealed.
Results from simulation-based experiments on geographical data demonstrate the excellent performance and the desired results have been obtained.
The proposed algorithm can be applied to solve other clustering problems in data mining.
American Psychological Association (APA)
Ji, Min& Xie, Fuding& Ping, Yu. 2013. A Dynamic Fuzzy Cluster Algorithm for Time Series. Abstract and Applied Analysis،Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-452589
Modern Language Association (MLA)
Ji, Min…[et al.]. A Dynamic Fuzzy Cluster Algorithm for Time Series. Abstract and Applied Analysis No. 2013 (2013), pp.1-7.
https://search.emarefa.net/detail/BIM-452589
American Medical Association (AMA)
Ji, Min& Xie, Fuding& Ping, Yu. A Dynamic Fuzzy Cluster Algorithm for Time Series. Abstract and Applied Analysis. 2013. Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-452589
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-452589