• DocumentCode
    2628267
  • Title

    Study on the Salinity Modeling Based on RBF Neural Network

  • Author

    Guodong, Gao ; Wenxiao, Zhang ; Guangyu, Mu

  • Author_Institution
    Dalian Ocean Univ., Dalian, China
  • Volume
    3
  • fYear
    2011
  • fDate
    6-7 Jan. 2011
  • Firstpage
    576
  • Lastpage
    578
  • Abstract
    A new RBF neural network is introduced and at the same time, its´ structure, feature and principium are also expatiated. Contrasting with BP neural network model, it has faster convergence and better precision when it is used in the salinity modeling. A BP neural network model is set up and trained in this paper, in order to approach compensate the effects of improves non-linearity. Test proves it is practical and dependable in the field of salinity modeling and has nice applied prospect.
  • Keywords
    aquaculture; backpropagation; radial basis function networks; BP neural network; RBF neural network; aquaculture; salinity measurement; salinity modeling; Automation; Mechatronics; RBF Neural network; Salinity; Simulation; model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Measuring Technology and Mechatronics Automation (ICMTMA), 2011 Third International Conference on
  • Conference_Location
    Shangshai
  • Print_ISBN
    978-1-4244-9010-3
  • Type

    conf

  • DOI
    10.1109/ICMTMA.2011.714
  • Filename
    5721551