A Novel Unsupervised Data-Driven Method for Electricity Theft Detection in AMI Using Observer Meters

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Bibliographic Details
Title: A Novel Unsupervised Data-Driven Method for Electricity Theft Detection in AMI Using Observer Meters
Authors: Ruobin Qi, Jun Zheng, Zhirui Luo, Qingqing Li
Source: IEEE Transactions on Instrumentation and Measurement. 71:1-10
Publisher Information: Institute of Electrical and Electronics Engineers (IEEE), 2022.
Publication Year: 2022
Subject Terms: 0203 mechanical engineering, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology
Document Type: Article
ISSN: 1557-9662
0018-9456
DOI: 10.1109/tim.2022.3189748
Rights: IEEE Copyright
Accession Number: edsair.doi...........f3093d57f524ffda26beee9d57b74e9d
Database: OpenAIRE
Description
ISSN:15579662
00189456
DOI:10.1109/tim.2022.3189748