Semisupervised Approach to Non Technical Losses Detection
Juan Tacón, Damián Melgarejo, Fernanda Rodríguez, Federico Lecumberry, Alicia Fernández
Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications , Lecture Notes in Computer Science Volume 8827, Springer, , page 698--705 - 2014
Research Group(s): Tratamiento de Imagenes (gti)
Department(s): Procesamiento de Señales
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Abstract

Non-technical electrical losses detection is a complex task, with high economic impact. Due to the diversity and large number of consumption records, it is very important to find an efficient automatic method to detect the largest number of frauds with the least amount of experts hours involved in preprocessing and inspections. This article analyzes the performance of a strategy based on a semisupervised method, that starting from a set of labeled data, extends this labels to unlabeled data, and then allows to detect new frauds at consumptions. Results show that the proposed framework, improves performance in terms of the F measure against manual methods performed by experts and previous supervised methods, avoiding hours of experts/inspection labeling.

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» Juan Tacón
» Fernanda Rodríguez
» Federico Lecumberry
» Alicia Fernández