Machine learning methods trained on simple models can predict critical transitions in complex natural systems

Forecasting sudden changes in complex systems is a critical but challenging task, with previously developed methods varying widely in their reliability. Here we develop a novel detection method, using simple theoretical models to train a deep neural network to detect critical transitions—the Early W...

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Detalles Bibliográficos

Autores principales:	Smita Deb, Sahil Sidheekh, Christopher F. Clements, Narayanan C. Krishnan, Partha S. Dutta
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	The Royal Society 2022-02-01
Colección:	Royal Society Open Science
Materias:	catastrophic transitions non-catastrophic transitions tipping points early warning indicators classification deep learning
Acceso en línea:	https://royalsocietypublishing.org/doi/10.1098/rsos.211475
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