Physics-informed deep learning to forecast $$\widehat{{\varvec{M}}}}_{{\varvec{m}}{\varvec{a}}{\varvec{x}}}$$ M ^ m a x during hydraulic fracturing
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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1 Online-Ressource.
- Sprache
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Englisch
- Erschienen in
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Physics-informed deep learning to forecast $$\widehat{{\varvec{M}}}}_{{\varvec{m}}{\varvec{a}}{\varvec{x}}}$$ M ^ m a x during hydraulic fracturing ; volume:13 ; number:1 ; day:12 ; month:8 ; year:2023 ; pages:1-9 ; date:12.2023
Scientific reports ; 13, Heft 1 (12.8.2023), 1-9, 12.2023
- Urheber
- Beteiligte Personen und Organisationen
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SpringerLink (Online service)
- DOI
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10.1038/s41598-023-40403-2
- URN
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urn:nbn:de:101:1-2024020710471818222570
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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15.08.2025, 07:28 MESZ
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Beteiligte
- Li, Ziyan
- Eaton, David W. S.
- Davidsen, Jörn
- SpringerLink (Online service)
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