• DocumentCode
    2440965
  • Title

    SVM-based Oil Security Pre-warning

  • Author

    Yong-bo Sun ; Hua Zhang ; Yong-heng Lu

  • Author_Institution
    Heilongjiang Inst. of Sci. & Technol.
  • fYear
    2008
  • fDate
    27-28 Dec. 2008
  • Firstpage
    55
  • Lastpage
    59
  • Abstract
    The highly efficient and accurate oil security pre-warning is of important significance for China, a big consumption nation, to establish the scientific safeguarding countermeasures. The SVM approach was employed herein to make empirical analysis on the oil security based on the optimal selection of oil security pre-warning indices. The results show that the oil security will be under the exposure of serious warning area in 2010, 2015, and 2020, which requires enhancing the security safeguarding measures. Finally the corresponding policies and suggestions were proposed based on the analysis above.
  • Keywords
    forecasting theory; petroleum industry; support vector machines; SVM-based oil security pre-warning; oil security pre-warning indices; optimal selection; scientific safeguarding countermeasures; support vector machines; Area measurement; Neural networks; Petroleum; Power generation economics; Rockets; Security; Statistics; Sun; Support vector machine classification; Support vector machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Modelling, Simulation and Optimization, 2008. WMSO '08. International Workshop on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-0-7695-3484-8
  • Type

    conf

  • DOI
    10.1109/WMSO.2008.68
  • Filename
    4756956