Hybrid Deep Learning Ensemble with Dynamic Fusion for Reliable Anomaly Detection in Operational LTE RANs.
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| Title: | Hybrid Deep Learning Ensemble with Dynamic Fusion for Reliable Anomaly Detection in Operational LTE RANs. |
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| Authors: | Kahoul, Abd El Madjid1, Bouraoui, Zakaria1, Zarour, Karim1, Boumezbeur, Insaf2 |
| Source: | Journal of Telecommunications & the Digital Economy. Dec2025, Vol. 13 Issue 4, p105-126. 22p. |
| Database: | Business Source Ultimate |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=bsu&AN=190605587 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.18080/jtde.v13n4.1363 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 22 StartPage: 105 Titles: – TitleFull: Hybrid Deep Learning Ensemble with Dynamic Fusion for Reliable Anomaly Detection in Operational LTE RANs. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Kahoul, Abd El Madjid – PersonEntity: Name: NameFull: Bouraoui, Zakaria – PersonEntity: Name: NameFull: Zarour, Karim – PersonEntity: Name: NameFull: Boumezbeur, Insaf IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 22031693 Numbering: – Type: volume Value: 13 – Type: issue Value: 4 Titles: – TitleFull: Journal of Telecommunications & the Digital Economy Type: main |
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