Retraction Note: Improving cloud efficiency through optimized resource allocation technique for load balancing using LSTM machine learning algorithm

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Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: 1 Online-Ressource.

Language: Englisch

Bibliographic citation: Retraction Note: Improving cloud efficiency through optimized resource allocation technique for load balancing using LSTM machine learning algorithm ; volume:12 ; number:1 ; day:6 ; month:12 ; year:2023 ; pages:1 ; date:12.2023
Journal of Cloud Computing ; 12, Heft 1 (6.12.2023), 1, 12.2023

Classification: Informatik

Creator: Ashawa, Moses
Douglas, Oyakhire
Osamor, Jude
Jackie, Riley

Contributor: SpringerLink (Online service)

DOI: 10.1186/s13677-023-00562-z

URN: urn:nbn:de:101:1-2024022214180033046650

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

Last update: 14.08.2025, 11:02 AM CEST

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Ashawa, Moses
Douglas, Oyakhire
Osamor, Jude
Jackie, Riley
SpringerLink (Online service)

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Application of a QPSO-optimized CNN-LSTM model in water quality prediction

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Retraction Note: Improving cloud efficiency through optimized resource allocation technique for load balancing using LSTM machine learning algorithm

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Other Objects (12)

Improving cloud efficiency through optimized resource allocation technique for load balancing using LSTM machine learning algorithm

LSTM-based traffic load balancing and resource allocation for an edge system

Application of a QPSO-optimized CNN-LSTM model in water quality prediction

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