Federated Learning‐Based Deep Stacked Autoencoder—Long Short‐Term Memory Model for Electric Vehicle Energy Demand Prediction.

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Bibliographic Details
Title: Federated Learning‐Based Deep Stacked Autoencoder—Long Short‐Term Memory Model for Electric Vehicle Energy Demand Prediction.
Authors: Mekala, K.1, mekalameiys@gmail.com, Sumathi, S.2, Gandhi, R.3, Shobana, S.4
Source: International Journal of Adaptive Control & Signal Processing; Apr2026, Vol. 40 Issue 4, p935-950, 16p
Database: Applied Science & Technology Source
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DbLabel: Applied Science & Technology Source
An: 192985371
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Federated Learning‐Based Deep Stacked Autoencoder—Long Short‐Term Memory Model for Electric Vehicle Energy Demand Prediction.
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Adaptive+Control+%26+Signal+Processing%22">International Journal of Adaptive Control & Signal Processing</searchLink>; Apr2026, Vol. 40 Issue 4, p935-950, 16p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=192985371
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1002/acs.70033
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      – Code: eng
        Text: English
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        PageCount: 16
        StartPage: 935
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      – TitleFull: Federated Learning‐Based Deep Stacked Autoencoder—Long Short‐Term Memory Model for Electric Vehicle Energy Demand Prediction.
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            NameFull: Mekala, K.
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            NameFull: Sumathi, S.
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            NameFull: Gandhi, R.
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            – D: 01
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              Text: Apr2026
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              Y: 2026
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              Value: 40
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