• DocumentCode
    3467228
  • Title

    Control planning of water pollution using GA -BP model

  • Author

    Jia, Lixia ; Zhu, Changjun

  • Author_Institution
    Coll. of Archit., Hebei Univ. of Eng., Handan, China
  • Volume
    2
  • fYear
    2009
  • fDate
    5-6 Dec. 2009
  • Firstpage
    287
  • Lastpage
    290
  • Abstract
    By combining GA (Genetic Algorithm), which has the advantage of global optimization, and RBF , which has the advantage of local optimization, the calculation accuracy and convergence rate of the traditional BP neural network are improved. So the hybrid algorithm based on genetic algorithm and BP algorithm, not only retains the original merits of the neural network, but also overcomes these shortcomings, and establishes water quality evaluation model. Xinyang Nanwan reservoir as an example to evaluate, the experimental results show that the hybrid algorithm model has evaluation of high precision, and can be applied to water quality evaluation. The simulation result shows this method has high convergent speed and easily oriented global optimization and is therefore of great practical value.
  • Keywords
    backpropagation; genetic algorithms; radial basis function networks; water pollution; GA-BP model; backpropagation; genetic algorithm; radial basis function network; water pollution; water quality evaluation; Artificial neural networks; Biological neural networks; Convergence; Educational institutions; Genetic algorithms; Genetic engineering; Neural networks; Neurons; Signal processing algorithms; Water pollution; BP neural network; genetic algorithm; water quality;
  • 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.2009.5413050
  • Filename
    5413050