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Authors: Félix Biscarri 1 ; Iñigo Monedero 1 ; Carlos León 1 ; Juan I. Guerrero 1 ; Jesús Biscarri 2 and Rocío Millán 2

Affiliations: 1 University of Seville, Spain ; 2 ENDESA Distribución, Spain

Keyword(s): Data mining, Power utilities, Fraud detection, Non-technical losses.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Biomedical Engineering ; Business Analytics ; Data Engineering ; Data Mining ; Databases and Information Systems Integration ; Datamining ; Enterprise Information Systems ; Health Information Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Strategic Decision Support Systems

Abstract: This paper deals with the characterization of customers in power companies in order to detect consumption Non-Technical Losses (NTL). A new framework is presented, to find relevant knowledge about the particular characteristics of the electric power customers. The authors uses two innovative statistical estimators to weigh variability and trend of the customer consumption. The final classification model is presented by a rule set, based on discovering association rules in the data. The work is illustrated by a case study considering a real data base.

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Paper citation in several formats:
Biscarri, F.; Monedero, I.; León, C.; Guerrero, J.; Biscarri, J. and Millán, R. (2009). A MINING FRAMEWORK TO DETECT NON-TECHNICAL LOSSES IN POWER UTILITIES. In Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 2: ICEIS; ISBN 978-989-8111-85-2; ISSN 2184-4992, SciTePress, pages 97-102. DOI: 10.5220/0001953300970102

@conference{iceis09,
author={Félix Biscarri. and Iñigo Monedero. and Carlos León. and Juan I. Guerrero. and Jesús Biscarri. and Rocío Millán.},
title={A MINING FRAMEWORK TO DETECT NON-TECHNICAL LOSSES IN POWER UTILITIES},
booktitle={Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 2: ICEIS},
year={2009},
pages={97-102},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001953300970102},
isbn={978-989-8111-85-2},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 2: ICEIS
TI - A MINING FRAMEWORK TO DETECT NON-TECHNICAL LOSSES IN POWER UTILITIES
SN - 978-989-8111-85-2
IS - 2184-4992
AU - Biscarri, F.
AU - Monedero, I.
AU - León, C.
AU - Guerrero, J.
AU - Biscarri, J.
AU - Millán, R.
PY - 2009
SP - 97
EP - 102
DO - 10.5220/0001953300970102
PB - SciTePress