• DocumentCode
    3731231
  • Title

    The mill load modeling of combined grinding system based on RBF neural networks

  • Author

    Chuanjiang Yu; Jianjun Zheng; Tao Shen

  • Author_Institution
    School of Electrical Engineering, University of Jinan, China
  • fYear
    2015
  • Firstpage
    2085
  • Lastpage
    2090
  • Abstract
    In order to get the mill load modeling of combined grinding system in normal working condition, this paper proposes a method based on the RBF neural network. The neural network uses three kinds of kernel functions that are Gauss kernel function, multiquadric kernel function and inverse multinuclear kernel function. Using the gradient descent method trains the neural network. With the comparison of three neural network´s fitting error, I´ve come to the conclusion that the RBF neural network based on Gauss function is more accurate.
  • Keywords
    "Artificial neural networks","Training"
  • Publisher
    ieee
  • Conference_Titel
    Chinese Automation Congress (CAC), 2015
  • Type

    conf

  • DOI
    10.1109/CAC.2015.7382848
  • Filename
    7382848