• DocumentCode
    2707152
  • Title

    Soft-sensing method based on modified ANN inversion and its application in erythromycin fermentation

  • Author

    Ding, Yuhan ; Liu, Guohai ; Dai, Xianzhong

  • Author_Institution
    Sch. of Electr. & Inf. Eng., Jiangsu Univ., Zhenjiang, China
  • fYear
    2012
  • fDate
    6-8 June 2012
  • Firstpage
    900
  • Lastpage
    905
  • Abstract
    In this paper, we modify the soft-sensing method based on ANN inversion. By using the non-state variables or the so-called function variables besides the state variables, the possibility in constructing the soft-sensing model will increase and the derivative order in soft-sensing model will be low. The simulation results verify that the soft-sensing method based on the modified ANN inversion is more accurate than the unmodified one.
  • Keywords
    biotechnology; fermentation; neural nets; pharmaceutical industry; artificial neural network; erythromycin fermentation; function variables; modified ANN inversion; soft-sensing method; state variables; Artificial neural networks; Educational institutions; Equations; Mathematical model; Noise; Sensors; Training; Soft sensing; erythromycin fermentation; modified ANN inversion;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Automation (ICIA), 2012 International Conference on
  • Conference_Location
    Shenyang
  • Print_ISBN
    978-1-4673-2238-6
  • Electronic_ISBN
    978-1-4673-2236-2
  • Type

    conf

  • DOI
    10.1109/ICInfA.2012.6246910
  • Filename
    6246910