234 citations · 245 across the 5 of their papers we have counts for
5 papers
Identifying Irregular Power Usage by Turning Predictions into Holographic Spatial Visualizations
Patrick Glauner, Niklas Dahringer, Oleksandr Puhachov +4
Power grids are critical infrastructure assets that face non-technical losses (NTL) such as electricity theft or faulty meters. NTL may range up to 40% of the total electricity dis…
The Top 10 Topics in Machine Learning Revisited: A Quantitative Meta-Study
Patrick Glauner, Manxing Du, Victor Paraschiv +5
Which topics of machine learning are most commonly addressed in research? This question was initially answered in 2007 by doing a qualitative survey among distinguished researchers…
Is Big Data Sufficient for a Reliable Detection of Non-Technical Losses?
Patrick Glauner, Angelo Migliosi, Jorge Meira +3
Non-technical losses (NTL) occur during the distribution of electricity in power grids and include, but are not limited to, electricity theft and faulty meters. In emerging countri…
Neighborhood Features Help Detecting Non-Technical Losses in Big Data Sets
Patrick Glauner, Jorge Meira, Lautaro Dolberg +4
Electricity theft is a major problem around the world in both developed and developing countries and may range up to 40% of the total electricity distributed. More generally, elect…
The Challenge of Non-Technical Loss Detection using Artificial Intelligence: A Survey
Patrick Glauner, Jorge Augusto Meira, Petko Valtchev +2
Detection of non-technical losses (NTL) which include electricity theft, faulty meters or billing errors has attracted increasing attention from researchers in electrical engineeri…