The rapid development of urbanization has led to the gradual emergence of more traffic problems emerging; traffic incidents continue to increase in number and scope, and safety has become a serious issue. With the steady increase of vehicles and the contradiction between the supply and demand of road transportation, efficient solutions to traffic congestion and safety are paramount; intelligent transportation systems are the key to improving urban traffic. Based on the intelligent transportation decision system, this paper briefly discusses how to use business intelligence to conduct big data mining and analysis using data warehouses and online analytical processing technology to realize the automation of data reports, analyze the causes of traffic accidents, make scientific predictions of possible accidents, improve road capacity, and enhance the intelligence and informatization of the transportation decision system.


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    Titel :

    Intelligent Transportation Decision System Based on Big Data Mining


    Beteiligte:
    Sun, Ping (Autor:in) / Zhang, Yifan (Autor:in) / Gao, Zhen (Autor:in)

    Kongress:

    17th COTA International Conference of Transportation Professionals ; 2017 ; Shanghai, China


    Erschienen in:

    CICTP 2017 ; 205-214


    Erscheinungsdatum :

    18.01.2018




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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