Novosibirsk State University Journal of Information Technologies
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All Issues >> Contents: Volume 13, Issue No 2 (2015)

Forecasting of dynamic processes on the earth surface based on data assimilation
Artem Sergeyevich Feoktistov, Evgeny Semenovich Nezhevenko

Novosibirsk State University
Institute of Automation and Electrometry SB RAS

Abstract
A method of modeling a dynamic process on the Earth surface, such as wildfires, floods, mudslides, oil spills, in the conditions of a priori uncertainty is proposed. This method is based on the data assimilation approach. Data assimilation is realized using recurrent neural networks and Kalman filtering. The training process of the neural network is described and also we propose a method for accelerating neural network training through the using of a Kalman filter. The efficiency of its application is analyzed.

Key Words
computer simulation, wildfire, recurrent neural network, data assimilation, Kalman filter, 519.6

How to cite:
Feoktistov A. S., Nezhevenko E. S. Forecasting of dynamic processes on the earth surface based on data assimilation // Vestnik NSU Series: Information Technologies. - 2015. - Volume 13, Issue No 2. - P. 226-231. - ISSN 1818-7900. (in Russian).

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References
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Publication information
Main title Vestnik NSU Series: Information Technologies, Volume 13, Issue No 2 (2015).
Parallel title: Novosibirsk State University Journal of Information Technologies Volume 13, Issue No 2 (2015).

Key title: Vestnik Novosibirskogo gosudarstvennogo universiteta. Seriâ: Informacionnye tehnologii
Abbreviated key title: Vestn. Novosib. Gos. Univ., Ser.: Inf. Tehnol.
Variant title: Vestnik NGU. Seriâ: Informacionnye tehnologii

Year of Publication: 2015
ISSN: 1818-7900 (Print), ISSN 2410-0420 (Online)
Publisher: Novosibirsk State University Press
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