• DocumentCode
    1702952
  • Title

    Water quality assessment based on BP network and its application

  • Author

    Hao Zhu-lin ; Zhang Yuan-yuan ; Feng Min-quan

  • Author_Institution
    Key Lab. of Northwest Water Resources & Environ. Ecology of Educ. Minist., Xi´an Univ. of Technol., Xi´an, China
  • Volume
    2
  • fYear
    2011
  • Firstpage
    872
  • Lastpage
    876
  • Abstract
    The multilayer feed forward neural network (BP network) method was applied to evaluate water quality in order to determine the water quality in Fen river of Yuncheng section. Surface water limits of worse than V water was defined. Training sample was generated based on classification standard, then the water quality was evaluated by BP network that could be trained in Fen river of Yuncheng section. The water is polluted seriously in Fen river of Yuncheng section, The water quality is the standard of Worse than grade V in Xinjiang Zhanli monitoring section and Hejin Bridge monitoring section during 2005-2009. There is no time to delay the Implementation of pollution gross control. The BP network model can make full use of the water quality data to establish the complex nonlinear relationship between input and output. Large number of parameters in the network are obtained by learning, not given by man-made so that influence of human factors are avoided. The evaluation results are more objective and reasonable.
  • Keywords
    backpropagation; environmental science computing; multilayer perceptrons; rivers; water quality; water resources; Fen river; Yuncheng section; backpropagation network; multilayer feedforward neural network; water pollution; water quality assessment; Artificial neural networks; Indexes; Monitoring; Quality assessment; Rivers; Water pollution; Water resources; BP network; Fen River; the comprehensive water quality identification index; water quality assessment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Water Resource and Environmental Protection (ISWREP), 2011 International Symposium on
  • Conference_Location
    Xi´an
  • Print_ISBN
    978-1-61284-339-1
  • Type

    conf

  • DOI
    10.1109/ISWREP.2011.5893150
  • Filename
    5893150