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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Bibliographic Details
Main Author: Hussain, Saddam
Format: Thesis
Published: 2022
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