• DocumentCode
    3207590
  • Title

    Application of feedforward neural networks for soft sensors in the sugar industry

  • Author

    Devogelaere, Dirk ; Rijckaert, Marcel ; Leon, Osvaldo Goza ; Lemus, Gil Cruz

  • Author_Institution
    Chem. Eng. Dept., Katholieke Univ., Leuven, Belgium
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    2
  • Lastpage
    6
  • Abstract
    Neural networks have been successfully applied as intelligent sensors for process modeling and control. In this paper, the application of soft sensors in the cane sugar industry is discussed. A neural network is trained on historical data to predict process quality variables so that it can replace the lab-test procedure. An immediate benefit of building intelligent sensors is that the neural network can predict product quality in a timely manner.
  • Keywords
    feedforward neural nets; food processing industry; intelligent sensors; process control; quality control; feedforward neural networks; intelligent sensors; nonlinear black-box prediction; process control; quality control; soft sensors; sugar industry; Chemical engineering; Chemical sensors; Distributed control; Feedforward neural networks; Intelligent networks; Intelligent sensors; Investments; Neural networks; Process control; Sugar industry;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2002. SBRN 2002. Proceedings. VII Brazilian Symposium on
  • Print_ISBN
    0-7695-1709-9
  • Type

    conf

  • DOI
    10.1109/SBRN.2002.1181426
  • Filename
    1181426