CASPIAN SEA LEVEL PREDICTION USING ARTIFICIAL NEURAL NETWORK AND EMPIRICAL MODE DECOMPOSITION

CASPIAN SEA LEVEL PREDICTION USING ARTIFICIAL NEURAL NETWORK AND EMPIRICAL MODE DECOMPOSITION

This paper demonstrates the possibility of using nonlinear modeling for prediction of the Caspian Sea level. Phase space geometry of the of a model can be reconstructed by the embedology methods. Dynamical invariants, such as the Lyapunov exponents, the Kaplan-Yorke dimension, and the prediction hor...

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Bibliographic Details
Main Authors: Nikolai Makarenko, Lyailya Karimova, Olga Kruglun
Format: Article
Language:English
Published: Lomonosov Moscow State University 2010-12-01
Series:Geography, Environment, Sustainability
Subjects:
caspian sea level
fractal approximation
multifractal analysis
empirical mode decomposition
embedology
nonlinear prediction
Online Access:https://ges.rgo.ru/jour/article/view/235

Internet

https://ges.rgo.ru/jour/article/view/235

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