A deep-learning model for urban traffic flow prediction with traffic events mined from twitter

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Location: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 1573-1413

Extent: Online-Ressource

Language: Englisch

Notes: online resource.

Bibliographic citation: A deep-learning model for urban traffic flow prediction with traffic events mined from twitter ; day:14 ; month:3 ; year:2020 ; pages:1-24
World wide web ; (14.3.2020), 1-24

Classification: Handel, Kommunikation, Verkehr

Creator: Essien, Aniekan
Petrounias, Ilias
Sampaio, Pedro
Sampaio, Sandra

Contributor: SpringerLink (Online service)

DOI: 10.1007/s11280-020-00800-3

URN: urn:nbn:de:101:1-2020053103044058301129

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 14.08.2025, 10:56 AM CEST

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Essien, Aniekan
Petrounias, Ilias
Sampaio, Pedro
Sampaio, Sandra
SpringerLink (Online service)

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A deep-learning model for urban traffic flow prediction with traffic events mined from twitter

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Other Objects (12)

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Traffic and road conditions monitoring system using extracted information from Twitter

Dimensions management of traffic big data for short-term traffic prediction on suburban roadways

Traffic shaping concepts for advanced traffic engineering

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