• DocumentCode
    2252176
  • Title

    A new water quality evaluation model based on simplified Hopfield neural network

  • Author

    Rong, Li ; Junfei, Qiao

  • Author_Institution
    School of Electric Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
  • fYear
    2015
  • fDate
    28-30 July 2015
  • Firstpage
    3530
  • Lastpage
    3535
  • Abstract
    The evaluation of water quality plays a very important part in water resources protection. Compared with other methods, Hopfield neural network can evaluate the water quality effectively. Aiming at the problem of complicated structure of Hopfield neural network, a simplified model is proposed. In the simplified model, connection weights are designed by singular value decomposition to improve running speed. And the simple structure is got by deleting unimportant weights. Finally, the effectiveness and feasibility of simplified model is proved for water quality evaluation.
  • Keywords
    Data models; Hopfield neural networks; Indexes; Neurons; Standards; Testing; Water pollution; Hopfield neural network; evaluation criteria; simplified model; water quality evaluation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (CCC), 2015 34th Chinese
  • Conference_Location
    Hangzhou, China
  • Type

    conf

  • DOI
    10.1109/ChiCC.2015.7260184
  • Filename
    7260184