Fast Non-Technical Losses Identification Through Optimum-Path Forest (original) (raw)

2009 15th International Conference on Intelligent System Applications to Power Systems, 2009

Abstract

Abstract Fraud detection in energy systems by illegal consumers is the most actively pursued study in non-technical losses by electric power companies. Commonly used supervised pattern recognition techniques, such as artificial neural networks and support vector machines have been applied for automatic commercial frauds identification, however they suffer from slow convergence and high computational burden. We introduced here the optimum-path forest classifier for a fast non-technical losses recognition, which has been ...

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