Exploring Deep Learning Approaches for Short-Term Passenger Demand Prediction
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource, 1 online resource.
- Sprache
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Englisch
- Erschienen in
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Exploring Deep Learning Approaches for Short-Term Passenger Demand Prediction ; volume:5 ; number:3 ; day:23 ; month:8 ; year:2023 ; pages:1-20 ; date:12.2023
Data science for transportation ; 5, Heft 3 (23.8.2023), 1-20, 12.2023
- Urheber
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Ghandeharioun, Zahra
Zendehdel Nobari, Parham
Wu, Wenhui
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
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10.1007/s42421-023-00075-w
- URN
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urn:nbn:de:101:1-2023110609291531807933
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 10:44 MESZ
Datenpartner
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Beteiligte
- Ghandeharioun, Zahra
- Zendehdel Nobari, Parham
- Wu, Wenhui
- SpringerLink (Online service)
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