Open AccessAn adaptive approach based on Bernstein polynomial to predict chaotic time series
Author(s) -
Hua Yan,
Pengcheng Wei,
Xin Xiao
Publication year - 2007
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.56.5111
Subject(s) - chaotic , series (stratigraphy) , computer science , convergence (economics) , bernstein polynomial , time series , mathematics , polynomial , algorithm , chaotic systems , mathematical optimization , artificial intelligence , machine learning , mathematical analysis , paleontology , economics , biology , economic growth
In this paper, we propose an approach using the Bernstein polynomial to model the dynamics of chaotic time series. Combining it with RLS algorithm, we can predict the chaotic time series adaptively. Theoretical analysis and computer simulation have demonstrated that this approach can provide high precision and satisfactory percentage of prediction for some typical chaotic time series. Because of the fast convergence of RLS algorithm, this approach can be applied to predicting short record chaotic time series in real time.