English

Electricity Theft Detection using Machine Learning

Cryptography and Security 2018-04-17 v1 Computers and Society Machine Learning

Abstract

Non-technical losses (NTL) in electric power grids arise through electricity theft, broken electric meters or billing errors. They can harm the power supplier as well as the whole economy of a country through losses of up to 40% of the total power distribution. For NTL detection, researchers use artificial intelligence to analyse data. This work is about improving the extraction of more meaningful features from a data set. With these features, the prediction quality will increase.

Keywords

Cite

@article{arxiv.1708.05907,
  title  = {Electricity Theft Detection using Machine Learning},
  author = {Niklas Dahringer},
  journal= {arXiv preprint arXiv:1708.05907},
  year   = {2018}
}
R2 v1 2026-06-22T21:18:43.517Z