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Machine learning surrogates for efficient hydrologic modeling: Insights from stochastic simulations of managed aquifer recharge

Fuente: arXiv

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Dettagli Bibliografici
Autori principali:	Dai, Timothy, Maher, Kate, Perzan, Zach
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Geophysics Machine Learning
Accesso online:	Acceder al recurso
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