Synthetic Theft Attacks and Long Short Term Memory-Based Preprocessing for Electricity Theft Detection Using Gated Recurrent Unit

Electricity theft is one of the challenging problems in smart grids. The power utilities around the globe face huge economic loss due to ET. The traditional electricity theft detection (ETD) models confront several challenges, such as highly imbalance distribution of electricity consumption data, cu...

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Bibliographic Details
Main Authors:	Asif, M. (Author), Aslam, S. (Author), Javaid, N. (Author), Javaid, S. (Author), Javed, M.U (Author), Pamir (Author), Yahaya, A.S (Author)
Format:	Article
Language:	English
Published:	MDPI 2022
Subjects:	Balancing Brain Crime Deep learning technique deep learning techniques Economic loss Electric power transmission networks Electric power utilization Electricity theft electricity theft detection Electricity theft detection False positive rates gated recurrent unit Gated recurrent unit Learning algorithms Learning techniques long short term memory Long short-term memory Losses machine learning techniques Machine learning techniques Power utility smart grids Smart power grids Theft attack theft attacks
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Synthetic Theft Attacks and Long Short Term Memory-Based Preprocessing for Electricity Theft Detection Using Gated Recurrent Unit

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