• DocumentCode
    536112
  • Title

    The Application of a Hybrid Model

  • Author

    Ailing, Chen

  • Author_Institution
    Sch. of Inf. Manage., Shandong Economic Univ., Jinan, China
  • Volume
    1
  • fYear
    2010
  • fDate
    23-24 Oct. 2010
  • Firstpage
    88
  • Lastpage
    90
  • Abstract
    In order to improve the prediction precision of flow stress, in view of intrinsic limitation of traditional models, a new method combining the combinative algorithm of group method and modified error function BP networks with mathematical models (Hybrid Model) to predict flow stress is proposed. By simulation, the results show that this method can correctly recur to the flow stress in the sampled data and it can also predict well the non-sampled data. The predicted results with this method are much better than those with the method combining neural networks with mathematical models.
  • Keywords
    backpropagation; mechanical engineering computing; plastic flow; steel; error function BP networks; flow stress; hybrid model; prediction precision; Artificial neural networks; Data models; Mathematical model; Predictive models; Steel; Strain; Stress; hybrid model; mathematical model; prediction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence and Computational Intelligence (AICI), 2010 International Conference on
  • Conference_Location
    Sanya
  • Print_ISBN
    978-1-4244-8432-4
  • Type

    conf

  • DOI
    10.1109/AICI.2010.25
  • Filename
    5656607