• DocumentCode
    442084
  • Title

    The research on integrated neural networks in rolling load prediction system for temper mill

  • Author

    He, Hai-tao ; Liu, Hong-Min

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Yanshan Univ., Qinhuangdao, China
  • Volume
    7
  • fYear
    2005
  • fDate
    18-21 Aug. 2005
  • Firstpage
    4089
  • Abstract
    In order to improve the predicting precision of rolling load, a new approach is proposed in which artificial neural network is integrated with theoretical rolling load model, and deformation resistance can be predicted based on measured data. Moreover, traditional self-learning is involved in the system. The practice has proved that the new method can predict the rolling load on temper mill with a high precision.
  • Keywords
    neural nets; rolling mills; tempering; unsupervised learning; artificial neural network; deformation resistance prediction; integrated neural network; rolling load prediction system; self learning; temper mill; theoretical rolling load model; Deformable models; Educational institutions; Electrical resistance measurement; Friction; Intelligent networks; Load modeling; Mathematical model; Milling machines; Neural networks; Predictive models; Rolling load; neural network; prediction; temper mill;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
  • Conference_Location
    Guangzhou, China
  • Print_ISBN
    0-7803-9091-1
  • Type

    conf

  • DOI
    10.1109/ICMLC.2005.1527653
  • Filename
    1527653