Research Article Open Access

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

Lekini Nkodo Claude Bernard1, Ndzana Benoît1 and Oumarou Hamandjoda1
  • 1 University of Yaounde I, Cameroon
American Journal of Engineering and Applied Sciences
Volume 10 No. 1, 2017, 32-42

DOI: https://doi.org/10.3844/ajeassp.2017.32.42

Submitted On: 9 September 2016 Published On: 6 January 2017

How to Cite: 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

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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Keywords

  • Fraud Detection
  • Support Vector Machine
  • Load Profile
  • Irregularities
  • Prediction