Electric theft detection using unsupervised machine learning-based matrix profile and K-means clustering technique
Electric theft is the major issue faced by utility companies in different countries as it causes significant revenue losses and affects the power grid reliability. This paper presents a novel electric theft detection framework based on an unsupervised machine learning technique employing matrix prof...
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Main Authors: | , , , |
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Format: | Book Section |
Published: |
Springer Science and Business Media Deutschland GmbH
2022
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Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/100581/ http://dx.doi.org/10.1007/978-981-16-8484-5_2 |
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