Neural network approach for robust and fast calculation of physical processes in numerical environmental models: compound parameterization with a quality control of larger errors

DOI10.1016/J.NEUNET.2007.12.019zbMath1254.86012DBLPjournals/nn/KrasnopolskyFTB08OpenAlexW2123313626WikidataQ31144754 ScholiaQ31144754MaRDI QIDQ1932017

Hendrik L. Tolman, Alexei A. Belochitski, Vladimir M. Krasnopolsky, Michael S. Fox-Rabinovitz

Publication date: 17 January 2013

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2007.12.019

zbMATH Keywords

wavesneural networksnumerical modelingdata assimilationclimateweather

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Meteorology and atmospheric physics (86A10) Applications to the sciences (65Z05)

Related Items (1)

Non-linear wave data assimilation with an ANN-type wind-wave model and ensemble Kalman filter (EnKF)

This page was built for publication: Neural network approach for robust and fast calculation of physical processes in numerical environmental models: compound parameterization with a quality control of larger errors