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

American journal of engineering and applied sciences

Bernard, Lekini Nkodo Claude¹ 

关键词: Fraud Detection;    Support Vector Machine;    Load Profile;    Irregularities;    Prediction;   

DOI  :  10.3844/ajeassp.2017.32.42

学科分类：工程和技术（综合）

来源: Science Publications

【 摘 要 】

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.

【 授权许可】

CC BY