Multi-domain encoder–decoder neural networks for latent data assimilation in dynamical systems

High-dimensional dynamical systems often require computationally intensive physics-based simulations, making full physical space data assimilation impractical. Latent data assimilation methods perform assimilation in reduced-order latent space for efficiency but struggle with complex, nonlinear stat...

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Bibliographic Details

Published in:	Computer methods in applied mechanics and engineering Vol. 430; p. 117201
Main Authors:	Cheng, Sibo, Zhuang, Yilin, Kahouadji, Lyes, Liu, Che, Chen, Jianhua, Matar, Omar K., Arcucci, Rossella
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.10.2024 Elsevier
Subjects:	Computer Science Data assimilation Data fusion Deep learning Dynamical systems Environmental Sciences Nonlinear Sciences Physics Deep learning Data fusion Dynamical systems Data assimilation Data assimilation Deep learning Data fusion Dynamical systems
ISSN:	0045-7825, 1879-2138
Online Access:	Get full text
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