Bridging observations, theory and numerical simulation of the ocean using machine learning

Bridging observations, theory and numerical simulation of the ocean using machine learning

Progress within physical oceanography has been concurrent with the increasing sophistication of tools available for its study. The incorporation of machine learning (ML) techniques offers exciting possibilities for advancing the capacity and speed of established methods and for making substantial an...

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Podrobná bibliografie
Hlavní autoři: Maike Sonnewald, Redouane Lguensat, Daniel C Jones, Peter D Dueben, Julien Brajard, V Balaji
Médium: Článek
Jazyk:English
Vydáno: IOP Publishing 2021-01-01
Edice:Environmental Research Letters
Témata:
ocean science
physical oceanography
observations
theory
modelling
supervised machine learning
On-line přístup:https://doi.org/10.1088/1748-9326/ac0eb0

Internet

https://doi.org/10.1088/1748-9326/ac0eb0

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