Non-Technical Loss analysis for detection of electricity theft using support vector machines

Evaluation of Customer Behaviour Irregularities in Cameroon Electricity Network using Support Vector Machine

“…They are based on the search for the optimal hyper plane margin, when possible, class or correctly separates the data while being far away as possible from all observations. The principle is to find a classifier, or a discrimination function, the generalization ability (quality forecast) is the largest possible (Nagi et al, 2008b). That is to say, to bring the issue of discrimination in the linear, the search for an optimal hyper plane and two ideas or tricks achieve this objective (Nagi et al, 2010a;2010b):…”

A Comprehensive Study of Smart Grids

“…Utility grids lose large amounts of money each year due to electricity theft. Electricity theft can be defined as an illegal way of using electrical equipments or services without paying the bills, or to acquire reduced bills [10].…”

Fraud Detection in Electric Power Distribution Networks using an Ann-Based Knowledge-Discovery Process

“…E. W. S. dos Angelos [8] presented a cluster-based classification strategy with an unsupervised algorithm of two steps to identify suspected profiles of power consumption, providing a good assertiveness in real life systems. Over the past years, other studies in this field have been addressed applying different computational techniques to improve the detection of non-technical losses [9][10][11][12][13].…”