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Ponencia
A data mining method based on the variability of the customer consumption. A special application on electric utility companies
Autor/es | Biscarri Triviño, Félix
Monedero Goicoechea, Iñigo Luis León de Mora, Carlos Guerrero Alonso, Juan Ignacio Biscarri Triviño, Jesús Millán, Rocío |
Departamento | Universidad de Sevilla. Departamento de Tecnología Electrónica |
Fecha de publicación | 2008 |
Fecha de depósito | 2022-03-24 |
Publicado en |
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ISBN/ISSN | 978-989-8111-37-1 2184-4992 |
Resumen | This paper describes a method proposed in order to recover electrical energy (lost by abnormality or fraud)
by means of a data mining analysis based in outliers detection. It provides a general methodology to obtain a
list ... This paper describes a method proposed in order to recover electrical energy (lost by abnormality or fraud) by means of a data mining analysis based in outliers detection. It provides a general methodology to obtain a list of abnormal users using only the general customer databases as input. The hole input information needed is taken exclusively from the general customers’ database. The data mining method has been successfully applied to detect abnormalities and fraudulencies in customer consumption. We provide a real study and we include a number of abnormal pattern examples. |
Cita | Biscarri Triviño, F., Monedero Goicoechea, I.L., León de Mora, C., Guerrero Alonso, J.I., Biscarri Triviño, J. y Millán, R. (2008). A data mining method based on the variability of the customer consumption. A special application on electric utility companies. En ICEIS 2008: 10th International Conference on Enterprise Information Systems (370-374), Barcelona, España: SciTePress. |
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