Detection of Non-Technical Losses Using SOSTLink and Bidirectional Gated Recurrent Unit to Secure Smart Meters
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Title
Detection of Non-Technical Losses Using SOSTLink and Bidirectional Gated Recurrent Unit to Secure Smart Meters
Authors
Keywords
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Journal
Applied Sciences-Basel
Volume 10, Issue 9, Pages 3151
Publisher
MDPI AG
Online
2020-05-04
DOI
10.3390/app10093151
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- (2018) Xavi Masip-Bruin et al. Future Generation Computer Systems-The International Journal of eScience
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