Neural Networks for Chaotic Time Series Forecasting

Golovko, Vladimir; Savitsky, Yury

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Автор

Golovko, Vladimir
Savitsky, Yury

Дата издания

2001

Издательство

BSUIR

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Библиографическое описание

Golovko, V. Neural Networks for Chaotic Time Series Forecasting / Vladimir Golovko, Yury Savitsky // The 2nd International Conference on Neural Networks and Artificial Intelligence : proceedings, Minsk, October 2–5, 2001 / Belarusian State University of Informatics and Radioelectronicsb ; ed.: Rauf Kh. Sadykhov [et al.]. – Minsk, 2001. – P. 70–74 : il. – Bibliogr.: p. 74 (10 titles).

Аннотация

This paper examines neural network in order to predict behavior o f chaotic systems. The prediction is performed both on the level o f emergent structures and on the level o f individual data points. The network is tested using the Henon and Lorenz chaotic time series. The results o f experiments and future directions are discussed.