Modeling systems from partial observations

Modeling systems from partial observations

Modeling systems from collected data faces two main difficulties: the first one concerns the choice of measurable variables that will define the learnt model features, which should be the ones concerned by the addressed physics, optimally neither more nor less than the essential ones. The second one...

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Bibliographic Details
Main Authors: Victor Champaney, Víctor J. Amores, Sevan Garois, Luis Irastorza-Valera, Chady Ghnatios, Francisco J. Montáns, Elías Cueto, Francisco Chinesta
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-10-01
Series:Frontiers in Materials
Subjects:
partial observability
AI
machine learning
recurrent NN
LSTM
static condensation
Online Access:https://www.frontiersin.org/articles/10.3389/fmats.2022.970970/full

Internet

https://www.frontiersin.org/articles/10.3389/fmats.2022.970970/full

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