• DocumentCode
    1987004
  • Title

    Application of Spatial Data Mining in Accident Analysis System

  • Author

    Wang Jinlin ; Chen Xi ; Zhou Kefa ; Wang Wei ; Zhang Dan

  • Author_Institution
    Xinjiang Inst. of Geogr. & Ecology, Chinese Acad. of Sci., Urumqi
  • Volume
    1
  • fYear
    2008
  • fDate
    21-22 Dec. 2008
  • Firstpage
    472
  • Lastpage
    475
  • Abstract
    Traffic accidents cause enormous losses for our country and plenty of national assets drain away every year, and therefore the task of traffic management is weightier than Mount Tai, but the complexity of traffic accident analysis has brought many difficulties to traffic management and decision-making. A three-layer analysis system based on spatial data mining of GIS is proposed in this paper, this three-layer architecture displays the whole process of accident data extracting, preprocessing and mining and it applies spatial data mining to GIS, which will certainly further expand the width and depth of GIS application field. Finally, this paper introduces the method of developing traffic accident analysis system by using ArcGIS Engine and C#.NET and gives the class realization of system main functions.
  • Keywords
    data mining; decision making; geographic information systems; network operating systems; road accidents; road safety; road traffic; traffic engineering computing; ArcGIS Engine; C#.NET; GIS; accident data extraction; decision-making; spatial data mining; three-layer analysis system; traffic accident analysis system; traffic management; Application software; Asset management; Data mining; Displays; Engines; Geographic Information Systems; Management training; Programming; Road accidents; Technology management; Accidents cause; ArcGIS Engine; Spatial Data Mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Education Technology and Training, 2008. and 2008 International Workshop on Geoscience and Remote Sensing. ETT and GRS 2008. International Workshop on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-0-7695-3563-0
  • Type

    conf

  • DOI
    10.1109/ETTandGRS.2008.253
  • Filename
    5070198