• DocumentCode
    3108676
  • Title

    An Improved OIF Elman Neural Network Model with Direction Profit Factor and Its Applications

  • Author

    Li, Ming ; Wang, Limin ; Liu, Yang ; Liu, Ying ; Sun, Qian ; Han, Xuming

  • Author_Institution
    Dept. of Inf., Changchun Taxation Coll., Changchun, China
  • fYear
    2009
  • fDate
    28-30 Dec. 2009
  • Firstpage
    208
  • Lastpage
    211
  • Abstract
    Output-input feedback (OIF) Elman neural network is a dynamic feedback network. An improved model is proposed based on the OIF Elman neural network by introducing direction profit factor in this paper. Moreover, the proposed model is applied to forecast the composite index of stock. In addition, some comparisons are also made when the stock exchange is performed using prediction results from OIF Elman neural network. Simulation results show that the proposed model is feasible and effective in the finance field. It shows that the proposed model can not only improve the forecasting precision evidently and possess the characteristic of quick convergence but also provide a good reference tool for investors to obtain more profits.
  • Keywords
    profitability; recurrent neural nets; stock markets; direction profit factor; dynamic feedback network; output-input feedback Elman neural network; stock composite index forecasting; stock exchange; Application software; Artificial neural networks; Computer networks; Finance; Machine vision; Neural networks; Neurofeedback; Predictive models; State feedback; Stock markets; OIF Elman neural network; composite index of stock; direction profit factor; forecast;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Vision, 2009. ICMV '09. Second International Conference on
  • Conference_Location
    Dubai
  • Print_ISBN
    978-0-7695-3944-7
  • Electronic_ISBN
    978-1-4244-5645-1
  • Type

    conf

  • DOI
    10.1109/ICMV.2009.39
  • Filename
    5381114