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Electricity Theft Detection using Machine Learning (1708.05907v1)

Published 19 Aug 2017 in cs.CR, cs.CY, and cs.LG

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.

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