Machine learning classification algorithms and anomaly detection in conventional meters and Tunisian electricity consumption large datasets-Reference-Cited by-同舟云学术

Machine learning classification algorithms and anomaly detection in conventional meters and Tunisian electricity consumption large datasets

Published:2021-09 Issue: Volume:94 Page:107329
ISSN:0045-7906
Container-title:Computers & Electrical Engineering
language:en
Short-container-title:Computers & Electrical Engineering

Author:

Oprea Simona-Vasilica,Bâra Adela

Funder

Unitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si Inovarii

Colegiul Consultativ pentru Cercetare-Dezvoltare şi Inovare

Ontario Ministry of Research, Innovation and Science

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,General Computer Science,Control and Systems Engineering

Reference24 articles.

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4. Review of non-technical loss detection methods;Messinis;Electr Power Syst Res,2018

5. Anomaly detection and visualization of school electricity consumption data;Cui,2017

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