• DocumentCode
    2183042
  • Title

    Application of BP Neural Networks on Prediction of Operating Condition of Loom

  • Author

    Zhu, Yanhong ; He, Dongbin ; Duan, Liying

  • Author_Institution
    Shijiazhuang Posts & Telecommun. Tech. Coll., Shijiazhuang, China
  • Volume
    2
  • fYear
    2010
  • fDate
    29-31 Oct. 2010
  • Firstpage
    91
  • Lastpage
    94
  • Abstract
    In order to forecast quickly the operating condition of the loom, optimize the parameters of loom production, so that the production efficiency of loom will be improved. This paper studies the prediction of the operating condition of the loom based on the neural networks. The neural networks technology is applied to forecast the operating condition of the loom production, establishes corresponding prediction model of loom production. With the help of neural networks samples are trained and checked, then are applied to forecast the operating condition of the loom production, the results are compared with the Bayesian theorem. The study indicates that network model based on the neural networks has reliability and high accuracy.
  • Keywords
    Bayes methods; backpropagation; neural nets; production equipment; BP neural networks; Bayesian theorem; loom operating condition prediction; loom production efficiency; BP neural network; bayesian theorem; prediction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Design (ISCID), 2010 International Symposium on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4244-8094-4
  • Type

    conf

  • DOI
    10.1109/ISCID.2010.111
  • Filename
    5692741