Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/25142
Title: Traffic flow data mining and evaluation based on fuzzy clustering techniques
Authors: Hu, C
Luo, N
Yan, X
Shi, W 
Keywords: Cluster validity
Fuzzy clustering
Similarity measure
Traffic flow
Issue Date: 2011
Source: International journal of fuzzy systems, 2011, v. 13, no. 4, p. 344-349 How to cite?
Journal: International journal of fuzzy systems 
Abstract: Effective mining technology can extract the spatial distribution pattern of the road network traffic flow. In this paper, the similarities between traffic flow objects with spatial temporal characteristics were measured by introducing the Dynamic Time Warping (DTW) and the shortest path analysis method. We proposed a new fuzzy clustering algorithm for road network traffic flow data. So that traffic flow data objects with similar properties and space correlation are clustered into a group, which find the spatial distribution pattern of road traffic flow. The experimental results show that the method was valid and effective. The road network was classified reasonably, and classification results could provide traffic zone division with decision auxiliary support.
URI: http://hdl.handle.net/10397/25142
ISSN: 2199-3211
EISSN: 1562-2479
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