• DocumentCode
    3166027
  • Title

    Application of BP neural network to determine of mine water inrush sources based on Matlab

  • Author

    Li, Jianlin ; Zhang, Hongyun

  • Author_Institution
    Instituite of Resources & Environ., Henan Polytech. Univ., Jiaozuo, China
  • fYear
    2011
  • fDate
    8-10 Aug. 2011
  • Firstpage
    179
  • Lastpage
    182
  • Abstract
    Because of the developing environment, the occurring conditions and the randomness, uncertainty and fuzziness of mine water inrush, it is a very complex nonlinear system to determination of mine water inrush sources. Artificial neural network is of the stronger self-organization, self-adaptability and self-learning capability, which is specially suited to solve nonlinear problems. In the paper, we analyzed fristly the chemical characteristic of aquifer of certain mine. 78 samples of pit water as the training sample survey and other 31 samples of pit water as test samples, BP neural network based on Matlab was set up and applied in the mine water to determine of mine water inrush sources. The model gains a better application in practical projects and the accuracy of the assessment is above 90%. It is simple and its assessment results are note easily affected by the human factors. So BP neural network based on Matlab is effective and is worth to popularization and application to determine of mine water inrush sources.
  • Keywords
    backpropagation; groundwater; neural nets; water resources; water supply; BP neural network; Matlab; aquifer; artificial neural network; chemical characteristic; mine water inrush source; self-adaptability; self-learning capability; self-organization; Biological neural networks; Coal; Floors; Mathematical model; Surges; Training; Water resources; BP neural network; Matlab; determination of mine water inrush sources; mine water inrush;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on
  • Conference_Location
    Deng Leng
  • Print_ISBN
    978-1-4577-0535-9
  • Type

    conf

  • DOI
    10.1109/AIMSEC.2011.6010199
  • Filename
    6010199