• DocumentCode
    2100858
  • Title

    Application of Chaotic Time Series Prediction in Forecasting of Library Borrowing Flow

  • Author

    Tian, Mei

  • Author_Institution
    Manage. Inst., Xinxiang Med. Univ., Xinxiang, China
  • fYear
    2011
  • fDate
    17-18 Sept. 2011
  • Firstpage
    557
  • Lastpage
    559
  • Abstract
    Prediction of library borrowing flow plays an important role in controlling the quality of book collection and cataloging work in library. Traditional time series prediction methods are hard to model the library borrowing flow because it is a nonlinear dynamical process and has nonstationary and stochastic character. Based on support vector machine and the theory of chaotic time series prediction, a new method is proposed to model and predict the library borrowing flow. The experiments show this method is reasonable to solve the nonlinear problem in library borrowing flow and is of certain value in both theory and practice.
  • Keywords
    cataloguing; chaos; libraries; stochastic processes; support vector machines; time series; book collection; cataloging work; chaotic time series prediction; library borrowing flow forecasting; nonlinear dynamical process; stochastic character; support vector machine; Computational modeling; Educational institutions; Libraries; Mathematical model; Predictive models; Support vector machines; Time series analysis; Chaotic time series; Library borrowing flow; Support vector machine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Internet Computing & Information Services (ICICIS), 2011 International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4577-1561-7
  • Type

    conf

  • DOI
    10.1109/ICICIS.2011.147
  • Filename
    6063325