Traffic flow data mining and evaluation based on fuzzy clustering techniques

Chunchun Hu, Nianxue Luo, Xiaohong Yan, Wen Zhong Shi

Research output: Journal article publicationJournal articleAcademic researchpeer-review

19 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)344-349
Number of pages6
JournalInternational Journal of Fuzzy Systems
Issue number4
Publication statusPublished - 1 Dec 2011


  • Cluster validity
  • Fuzzy clustering
  • Similarity measure
  • Traffic flow

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Software
  • Computational Theory and Mathematics
  • Artificial Intelligence


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