• DocumentCode
    3286256
  • Title

    Study on Application of Data Mining Technology to Modern Logistics Management Decision

  • Author

    Congna, Quan ; Huifeng, Zhao ; Bo, Li

  • Author_Institution
    Sch. of Bus., Agric. Univ. of Hebei, Baoding, China
  • Volume
    3
  • fYear
    2009
  • fDate
    15-17 May 2009
  • Firstpage
    433
  • Lastpage
    436
  • Abstract
    With the informationization, networking and intelligent development of modern logistics, the enormous data together with very critical knowledge hidden therein are generated from the management process of logistics enterprises. The data mining methods such as clustering, association rules, sequential pattern, statistics analysis, characteristics rules and so on can be used to find out the useful knowledge, enabling such data to become the real fortune of logistics companies and support their decisions and development. This paper introduces the significance of the application of data mining to modern logistics management decision, and then analyses in detail how to apply the data mining to modern logistics management decision and the key technology of the application. Finally, it is pointed out that the data mining technology is becoming more and more powerful in modern logistics management.
  • Keywords
    data mining; database management systems; decision support systems; information management; logistics data processing; statistical analysis; data mining technology; database management system; decision support system; logistics company; modern logistics management decision; scientific information management; statistical analysis technology; Association rules; Companies; Data mining; Energy management; Intelligent networks; Knowledge management; Logistics; Pattern analysis; Statistical analysis; Technology management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology and Applications, 2009. IFITA '09. International Forum on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-0-7695-3600-2
  • Type

    conf

  • DOI
    10.1109/IFITA.2009.93
  • Filename
    5232153