SUPERVISED MACHINE LEARNING FOR ELECTRICITY THEFT DETECTION: A SYSTEMATIC REVIEW OF TRENDS, CHALLENGES, AND FUTURE DIRECTIONS
Electricity theft causes substantial financial losses and grid instability, requiring data-driven detection solutions, especially through supervised machine learning (SML) techniques. This review systematically examines 50 studies (2012–2024) from Scopus, IEEE Xplore, and Web of Science, following PRISMA guidelines to...