• DocumentCode
    2872792
  • Title

    Application of BP-ANN in Forecasting the Equivalent Radon Exhalation Rate of Uranium Ore-Rock in the Course of Mine Ventilation

  • Author

    Ye, Yongjun ; Ding, Dexin ; Li, Xiangyang ; Zhou, Xinhuo ; Tan, Yan

  • Author_Institution
    Key Discipline Lab. for Nat. Defence for Biotechnol. in Uranium Min. & Hydrometallurgy, Univ. of South China, Hengyang, China
  • fYear
    2009
  • fDate
    11-13 Dec. 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    The process of radon exhalation of uranium ore-rock in the course of mine ventilation is a complex nonlinear dynamic system. In view of the ability of BP-ANN in dealing with the complex nonlinear function, taking the ventilation air quantity and wind pressure as the input vectors of the BP-ANN forecasting model, and the equivalent radon exhalation rate as the input vector, the paper established a predicting model of the equivalent radon exhalation rate of uranium ore-rock in the course of mine ventilation based on BP-ANN. The forecasting results are compared with that of the nonlinear regressive forecasting mode, which shows that the forecasting model of BPANN has higher predicting precission. It is feasible to forecast the equivalent radon exhalation rate of uranium ore-rock by the method.
  • Keywords
    backpropagation; mining; neural nets; nonlinear dynamical systems; radon; regression analysis; rocks; uranium; ventilation; BP-ANN forecasting model; Rn; U; backpropagation; complex nonlinear dynamic system; complex nonlinear function; equivalent radon exhalation rate forecasting; mine ventilation course; nonlinear regressive forecasting mode; prediction model; uranium ore-rock; ventilation air quantity; Artificial neural networks; Biotechnology; Brain modeling; Costs; Laboratories; Nonlinear dynamical systems; Nonlinear systems; Predictive models; Ventilation; Wind forecasting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-4507-3
  • Electronic_ISBN
    978-1-4244-4507-3
  • Type

    conf

  • DOI
    10.1109/CISE.2009.5366769
  • Filename
    5366769