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	Provedor de dados ArchiMer (1) Autor Chapron, Bertrand (1) Collard, Fabrice (1) Fablet, Ronan (1) Gaultier, Lucile (1) Herzet, Cedric (1) Ouala, Said (1) Pascual, Ananda (1) Mais... Palavra-chave Data assimilation (1) Data-driven models (1) Dynamical model (1) Interpolation (1) Kalman filter (1) Neural networks (1) Mais... Tipo do documento Text (1) Ano 2018 (1) País France (1) Idioma Inglês (1)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 1 Primeira ... 1 ... Última Neural Network Based Kalman Filters for the Spatio-Temporal Interpolation of Satellite-Derived Sea Surface Temperature ArchiMer Ouala, Said; Fablet, Ronan; Herzet, Cedric; Chapron, Bertrand; Pascual, Ananda; Collard, Fabrice; Gaultier, Lucile. The forecasting and reconstruction of oceanic dynamics is a crucial challenge. While model driven strategies are still the state-of-the-art approaches in the reconstruction of spatio-temporal dynamics. The ever increasing availability of data collections in oceanography raised the relevance of data-driven approaches as computationally efficient representations of spatio-temporal fields reconstruction. This tools proved to outperform classical state-of-the-art interpolation techniques such as optimal interpolation and DINEOF in the retrievement of fine scale structures while still been computationally efficient comparing to model based data assimilation schemes. However, coupling this data-driven priors to classical filtering schemes limits their potential... Tipo: Text Palavras-chave: Data assimilation; Dynamical model; Kalman filter; Neural networks; Data-driven models; Interpolation. Ano: 2018 URL: https://archimer.ifremer.fr/doc/00481/59286/61979.pdf Registros recuperados: 1 Primeira ... 1 ... Última

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