• DocumentCode
    3467168
  • Title

    Groundwater level prediction using ARMA-ANN model

  • Author

    Shi, Beixiao ; Zhu, Changjun

  • Author_Institution
    Hebei Univ. of Eng., Handan, China
  • Volume
    2
  • fYear
    2009
  • fDate
    5-6 Dec. 2009
  • Firstpage
    295
  • Lastpage
    298
  • Abstract
    At present, classic methods are often used to predict groundwater level, but the result is not ideal. Recent studies show that the combinational prediction methods have higher precision than single prediction methods. A combinational prediction model is presented based on ARMA and ANN neural network. And it is applied to comprehensive analysis and prediction of groundwater level. Case study indicates that precision of the model is rather high and its popularization significance is better than the other models, and has some practical value when being used in the dynamic groundwater level analysis.
  • Keywords
    groundwater; hydrological techniques; neural nets; ANN neural network; ARMA neural network; ARMA-ANN model; BP neural network; combinational prediction methods; groundwater level analysis; groundwater level prediction; Atmosphere; Equations; Neural networks; Prediction methods; Predictive models; Statistical analysis; Stochastic processes; Stochastic resonance; Time series analysis; Yttrium; ARMA; BP neural network; groundwater level;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Test and Measurement, 2009. ICTM '09. International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-4699-5
  • Type

    conf

  • DOI
    10.1109/ICTM.2009.5413048
  • Filename
    5413048