• DocumentCode
    3342236
  • Title

    Research on predictive control of coagulant dosage based on neural network

  • Author

    Zhe-Ying Song ; Xue-Ling Song ; Ying-Bao Zhao ; Chao-Ying Liu

  • Author_Institution
    Coll. of Electr. Eng. & Informational Sci., Hebei Univ. of Sci. & Technol., Shijiazhuang, China
  • Volume
    1
  • fYear
    2011
  • fDate
    26-28 July 2011
  • Firstpage
    217
  • Lastpage
    221
  • Abstract
    By analyzing the characters of coagulant dose process and factors related to coagulation, a predictive model of optimal coagulant dosage based on neural network is proposed in this paper. Historical data were used to simulate, the results show that this model is better than the traditional regression model. At last, an effective predictive control strategy of coagulant dosage is put forward based on this model, which offers an effective way for achieve the optimal coagulant dosing.
  • Keywords
    coagulation; neural nets; optimal control; predictive control; regression analysis; water treatment; neural network; optimal coagulant dosage process; predictive control model; regression model; Coagulation; Prediction algorithms; Predictive control; Predictive models; Pumps; Training; coagulant dosage; neural network; predictive control; regression model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2011 Seventh International Conference on
  • Conference_Location
    Shanghai
  • ISSN
    2157-9555
  • Print_ISBN
    978-1-4244-9950-2
  • Type

    conf

  • DOI
    10.1109/ICNC.2011.6022072
  • Filename
    6022072