Electricity Theft Detection in Incremental Scenario: A Novel Semi-supervised Approach based on Hybrid Replay Strategy

Deep learning (DL) has achieved great success in the field of electricity theft detection (ETD). Most existing studies have used supervised mode to complete the DL-based ETD, but they do not have the capability of incremental detection, especially in small sample size scenarios. To address this prob...

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Veröffentlicht in:	IEEE transactions on instrumentation and measurement Jg. 72; S. 1
Hauptverfasser:	Yao, Ruizhe, Wang, Ning, Ke, Weipeng, Liu, Zhili, Yan, Zhenhong, Sheng, Xianjun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.01.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Behavioral sciences Biological system modeling Boosting Convolutional neural networks Data models Deep learning Electricity Electricity theft detection Feature extraction Irish smart energy trial Support vector machines Temporal convolutional attention networks Theft Variational autoencoder
ISSN:	0018-9456, 1557-9662
Online-Zugang:	Volltext
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