- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
1 Online-Ressource.
- Language
-
Englisch
- Bibliographic citation
-
Potato Consumption Forecasting Based on a Hybrid Stacked Deep Learning Model ; day:15 ; month:7 ; year:2024 ; pages:1-25
Potato research ; (15.7.2024), 1-25
- Classification
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Wirtschaft
- Creator
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Eed, Marwa
Alhussan, Amel Ali
Qenawy, Al-Seyday T.
Osman, Ahmed M.
Elshewey, Ahmed M.
Arnous, Reham
- Contributor
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SpringerLink (Online service)
- DOI
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10.1007/s11540-024-09764-7
- URN
-
urn:nbn:de:101:1-2410012119266.605180662719
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:20 AM CEST
Data provider
This object is provided by:
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Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Eed, Marwa
- Alhussan, Amel Ali
- Qenawy, Al-Seyday T.
- Osman, Ahmed M.
- Elshewey, Ahmed M.
- Arnous, Reham
- SpringerLink (Online service)
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Sustainability and Potato Consumption
A Hybrid Clustering and Classification Technique for Forecasting Short-Term Energy Consumption
Forecasting household energy consumption based on lifestyle data using hybrid machine learning
A Hybrid Forecasting Approach
From Printed Devices to Vertically Stacked, 3D Flexible Hybrid Systems
Forecasting private consumption by consumer surveys
Forecasting private consumption by consumer surveys
A multi-granular stacked regression for forecasting long-term demand in Emergency Departments
Agrometeorological aspects of forecasting fields of potato within the E.C.
Deep learning-based forecasting of electricity consumption
Energy consumption forecasting in energy management systems