TY  - JOUR
AU  - Bernard, Lekini Nkodo Claude 
AU  - Benoît, Ndzana 
AU  - Hamandjoda, Oumarou 
PY  - 2017
TI  - Evaluation of Customer Behaviour Irregularities in Cameroon Electricity Network using Support Vector Machine
JF  - American Journal of Engineering and Applied Sciences
VL  - 10
IS  - 1
DO  - 10.3844/ajeassp.2017.32.42
UR  - https://thescipub.com/abstract/ajeassp.2017.32.42
AB  - 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.