Evaluation of Customer Behaviour Irregularities in Cameroon Electricity Network using Support Vector Machine
Lekini Nkodo Claude Bernard1, Ndzana Benoît1 & Oumarou Hamandjoda1 Show affiliations
- University of Yaounde I, Cameroon
American Journal of Engineering and Applied Sciences, Volume 10, Issue 1, pp. 32–42 · doi.org/10.3844/ajeassp.2017.32.42
Abstract
Non-Technical Losses (NTLs) in the Cameroonians electricity network are approximately 30 to 40% of production and are estimated at several billion CFA francs per year for National Electricity Company (ENEO); Hence the importance of finding effective solutions to fight against these losses. The purpose of this work was to develop a tool for the fraud detection for Cameroon National Electricity Company (ENEO) using support vector machines which consisted in data preprocessing base on the load profile, development of a model for classification, parameter optimization and detection of customers irregularities and prediction.
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Bernard, L. N. C., Benoît, N. & Hamandjoda, O. (2017). Evaluation of Customer Behaviour Irregularities in Cameroon Electricity Network using Support Vector Machine. American Journal of Engineering and Applied Sciences, 10(1), 32–42. https://doi.org/10.3844/ajeassp.2017.32.42
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