• DocumentCode
    2641984
  • Title

    Study on Risk Evaluation Intelligent Decision Support System of Urban Gas Pipeline

  • Author

    Liu, Jun E. ; Wang, Xin

  • Author_Institution
    Inf. Sch., Beijing Wuzi Univ., Beijing
  • fYear
    2008
  • fDate
    18-20 June 2008
  • Firstpage
    600
  • Lastpage
    600
  • Abstract
    Risk evaluation intelligent decision support system of urban gas pipeline is supposed to do risk evaluation on the whole system of urban gas pipelines. Based on the risk evaluation theory and took intelligent decision support system as a core, embedding the development model of geographical information system (GIS), it builds a general framework of intelligent decision support system under the GIS environment. The establishment of the system is an important tool to strengthen the scientific nature of making decisions for urban gas pipeline risk management, and to improve the management level of urban gas pipeline. Applying the theory of artificial intelligence, geographical information system and decision support system synthetically it designs the risk evaluation intelligent decision support system of urban gas pipeline to the overall structure. The results form a basis for further improvement and exploitation of such system.
  • Keywords
    decision support systems; gas industry; geographic information systems; knowledge based systems; neural nets; pipelines; risk analysis; artificial intelligence; decision making; geographical information system; intelligent decision support system; neural network; risk evaluation; risk management; urban gas pipeline; Artificial intelligence; Computational modeling; Decision making; Decision support systems; Geographic Information Systems; Intelligent structures; Intelligent systems; Machine intelligence; Pipelines; Risk management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Computing Information and Control, 2008. ICICIC '08. 3rd International Conference on
  • Conference_Location
    Dalian, Liaoning
  • Print_ISBN
    978-0-7695-3161-8
  • Electronic_ISBN
    978-0-7695-3161-8
  • Type

    conf

  • DOI
    10.1109/ICICIC.2008.527
  • Filename
    4603789