Mastering the characteristics of port ships traffic flow is the premise to plan, operate, and control waterway and navigation reasonably. Therefore, analysis of traffic flow characteristic of port ships is necessary and extremely important. Because Vessel traffic flow data acquisition methods are diverse, they contain flawed and incorrect data. To solve the problem, we made use of the improved K-means algorithm to prove the raw data of sequence samples. We applied data mining clustering analysis method to the Tianjin port ships traffic flow data characteristic for analysis. The results show that some valuable information is obtained by the proposed method which can also provide decision support for maritime safety administration.


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    Title :

    Based on the Improved K-Means Algorithm of Tianjin Port Traffic Flow Characteristic Analysis


    Contributors:
    Yan, Zhongzhen (author) / Yan, Xinping (author) / Huang, Ming (author) / Xie, Lei (author) / Wang, Zheyue (author)

    Conference:

    First International Conference on Transportation Information and Safety (ICTIS) ; 2011 ; Wuhan, China


    Published in:

    ICTIS 2011 ; 1863-1870


    Publication date :

    2011-06-16




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English





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