- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
1 Online-Ressource.
- Sprache
-
Englisch
- Erschienen in
-
Harnessing LSTM and XGBoost algorithms for storm prediction ; volume:14 ; number:1 ; day:18 ; month:5 ; year:2024 ; pages:1-13 ; date:12.2024
Scientific reports ; 14, Heft 1 (18.5.2024), 1-13, 12.2024
- Klassifikation
-
Wirtschaft
- Urheber
-
Frifra, Ayyoub
Maanan, Mohamed
Maanan, Mehdi
Rhinane, Hassan
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1038/s41598-024-62182-0
- URN
-
urn:nbn:de:101:1-2407291149262.124682955205
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 10:49 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Frifra, Ayyoub
- Maanan, Mohamed
- Maanan, Mehdi
- Rhinane, Hassan
- SpringerLink (Online service)
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