• DocumentCode
    3484013
  • Title

    Nonlinear prediction on maximum timings of complex time series

  • Author

    Kanno, Yoshitaka ; Ikeguchi, T.

  • Author_Institution
    Dept. of Inf. & Comput. Sci., Saitama Univ., Japan
  • Volume
    5
  • fYear
    2002
  • fDate
    18-22 Nov. 2002
  • Firstpage
    2350
  • Abstract
    We have already proposed a nonlinear modeling method which uses event sizes and event timings. In this paper, we consider availability of our method for continuous time series by predicting occurrence timing of maxima and their sizes from continuous time series. In order to evaluate availability of our scheme, we introduce the prediction accuracy by the following two methods. The first one is to predict continuous time series, using all information of the continuous time series. The second is to extract maxima from continuous time series and apply our proposed modeling scheme to the maxima of time series. Comparing these results, we show that our method has higher predictability if there exists an underlying dynamics of observed complex behavior.
  • Keywords
    continuous time systems; nonlinear systems; reliability; time series; complex time series; continuous time series; event sizes; event timings; maximum timings; nonlinear modeling method; nonlinear prediction; observed complex behavior; occurrence timing; prediction accuracy; Accuracy; Availability; Chaos; Data mining; Equations; Information analysis; Prediction algorithms; Predictive models; Time series analysis; Timing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on
  • Print_ISBN
    981-04-7524-1
  • Type

    conf

  • DOI
    10.1109/ICONIP.2002.1201914
  • Filename
    1201914