Seventh International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT'06)
A Clustering Algorithm for Time Series Data
Taipei, Taiwan
December 04-December 07
ISBN: 0-7695-2736-1
In the Intelligent Traffic System, the research about the analysis of time series of traffic flow is important and meaningful. Using clustering methods to analyze time series not only can find some typical patterns of traffic flow, but also can group the sections of highway by their different flow characteristics. In this paper, we propose an Encoded-Bitmap-approach-based swap method to improve the classic hierarchical method. Experiments show that the proposed method has a better performance on the change trend of time series than classic algorithm.
Index Terms:
Data Mining; Clustering; Time Series; Traffic Flow
Citation:
Jian Yin, Duanning Zhou, Qiong-Qiong Xie, "A Clustering Algorithm for Time Series Data," pdcat, pp.119-122, Seventh International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT'06), 2006