Comparing Machine and Deep Learning for Electricity Theft Detection from Monthly Billing Data in an Emerging Energy Market
This study addresses a regime-conditioned question in electricity theft detection: when only monthly billing series and inspection-confirmed labels are available, which supervised model families recover irregular consumption without relying on the temporal resolution of advanced metering infrastructure (AMI)? The worki...