• DocumentCode
    1677669
  • Title

    Prediction of Groundwater Quality Using Organic Grey Neural Network Model

  • Author

    Zhu, Changjun ; Zhou, Jihong ; Ju, Qin ; Dedong Liu

  • Author_Institution
    Coll. of Urban Constr., Hebei Univ. of Eng., Handan
  • fYear
    2008
  • Firstpage
    3168
  • Lastpage
    3171
  • Abstract
    In view of the defect that the gray method can only predict the tendency approximately and artificial neural network can not predict the future tendency really, a new organic gray neural network model was proposed by the advantages of GM(1,1),unbiased GM(1,1) and BP neural network. The two groups data got from the gray model are used as the input of the neural network and the origin data are used as the output of neural network. The neural network was trained to get the optimal structure of neural network. According to the dynamic law of groundwater quality in some region, the groundwater quality was predicted in organic gray neural network model. The results show that the model had highly fitting and predicting precision advantages than other model had.
  • Keywords
    backpropagation; environmental science computing; groundwater; neural nets; water pollution; BP neural network; artificial neural network; gray prediction; groundwater quality prediction; organic grey neural network model; Artificial neural networks; Differential equations; Educational institutions; Environmental management; Hydrology; Neural networks; Predictive models; Quality management; Resource management; Water resources;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The 2nd International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-1747-6
  • Electronic_ISBN
    978-1-4244-1748-3
  • Type

    conf

  • DOI
    10.1109/ICBBE.2008.1121
  • Filename
    4536001