Open Access
2013 A Dynamic Fuzzy Cluster Algorithm for Time Series
Min Ji, Fuding Xie, Yu Ping
Abstr. Appl. Anal. 2013(SI14): 1-7 (2013). DOI: 10.1155/2013/183410


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.


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Min Ji. Fuding Xie. Yu Ping. "A Dynamic Fuzzy Cluster Algorithm for Time Series." Abstr. Appl. Anal. 2013 (SI14) 1 - 7, 2013.


Published: 2013
First available in Project Euclid: 26 February 2014

zbMATH: 1272.68391
MathSciNet: MR3045053
Digital Object Identifier: 10.1155/2013/183410

Rights: Copyright © 2013 Hindawi

Vol.2013 • No. SI14 • 2013
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