In this paper, effective data mining methods are adopted for the tunnel management information system to deal with safety issue data and work out the relationship among these safety issues in order to estimate risk, establish intelligent decision support, provide basis of governance for railway maintenance departments and remedy the defects of the existed management information systems. In view of the bottleneck of Apriori algorithm, two new algorithms are proposed in this paper. The first is AprioriN algorithm based on arrays, which converts the operation on database to the operation on memory via coding. The second is a high performance association rule mining algorithm based on FP-tree, which accelerates the speed of traverse itemsets by adding an extra data structure. During the second scan of the database, a matrix is generated to save frequent 2-itemsets when the basic FP-tree is created. This paper attempts the improved algorithms to improve the efficiency.


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    Titel :

    Association rules algorithm and its application in the maintenance of the tunnel


    Beteiligte:
    Xu, W.X. (Autor:in) / Fan, Y.H. (Autor:in) / Zhang, J.X. (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2014


    Format / Umfang :

    14 Seiten, Bilder, Tabellen, 14 Quellen




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch




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