Intelligent feature engineered-machine learning based electricity theft detection framework for labelled and unlabelled datasets
Non-Technical Losses (NTLs) in electrical utilities, primarily related to electrical theft, significantly impact energy supplier companies and the nation’s overall economy. Power distribution companies worldwide rely on time-consuming, laborious, and inefficient random onsite inspections to catch an...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2022
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/102153/1/SaddamHussainPSKE2022.pdf.pdf |
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