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A method of non-linear time series prediction

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Języki publikacji
EN
Abstrakty
EN
The paper concerns time series modelling and prediction. Time series dynamics is described with the use of a hybrid linear-bilinear model. Then, a prediction algorithm that minimizes a variance of a prediction error is derived based on the hybrid linear-bilinear model, and the method of prediction strategy is proposed. The strategy is then applied to one of the most popular benchmark data -sunspot number series. Results obtained with the use of the model and the prediction algorithm proposed in the paper, are compared to the results obtained on the basis of a SETAR model proposed by Tong.
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Rocznik
Strony
11--16
Opis fizyczny
Bibliogr. 10 poz., wykr.
Twórcy
Bibliografia
  • [1] Astrom K., Introduction to stochastic control theory. Clarendon Press, Oxford 1993.
  • [2] Bielińska E., Identification of a mixed linear-bilinear diagonal time series model, Systems Science, Vol. 31, No. 3, 2005, pp. 21-36.
  • [3] Bielińska E., Methods of identification of elementary bilinear time series, Proc. 13 IEE IFAC Conference Methods and Models in Automation and Robotics, Vol. 1, 2007, pp. 559-564.
  • [4] Box G., Analiza szeregów czasowych, PWN, Warszawa 1983.
  • [5] Chen S., Billings S.A., Modeling and analysis of nonlinear time series, International Journal of Control, Vol. 49, 1989.
  • [6] Granger C.W., Andersen A., Nonlinear time series modeling, [in:] Applied time series analysis, Academic Press, 1978.
  • [7] Keyser R.M., Cauvernberge A.R., A self-tuning multi-step predictor application, Automatica, Vol. 17, 1981.
  • [8] Tong H., Non-linear time series, Clarendon Press, Oxford 1993.
  • [9] Wittenmark B., A self tuning predictor, IEEE Transaction on Automatic Control, Vol. AC-19, No. 6, 1974.
  • [10] Yaffee R., Introduction to time series analysis and forecasting, Academic Press, 2000.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BAT5-0033-0058
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