An efficient hybrid stock trend prediction system during COVID-19 pandemic based on stacked-LSTM and news sentiment analysis
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
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1573-7721
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Anmerkungen
-
online resource.
- Erschienen in
-
An efficient hybrid stock trend prediction system during COVID-19 pandemic based on stacked-LSTM and news sentiment analysis ; day:28 ; month:11 ; year:2022 ; pages:1-33
Multimedia tools and applications ; (28.11.2022), 1-33
- Klassifikation
-
Wirtschaft
- Urheber
-
Sharaf, Marwa
Hemdan, Ezz El-Din
El-Sayed, Ayman
El-Bahnasawy, Nirmeen A.
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1007/s11042-022-14216-w
- URN
-
urn:nbn:de:101:1-2023021109062734854764
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 11:02 MESZ
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Beteiligte
- Sharaf, Marwa
- Hemdan, Ezz El-Din
- El-Sayed, Ayman
- El-Bahnasawy, Nirmeen A.
- SpringerLink (Online service)
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