loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Félix Biscarri 1 ; Ignacio Monedero 1 ; Carlos León 1 ; Juán 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.

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 ; Industrial Applications of Artificial Intelligence ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: 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.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.116.85.108

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Biscarri, F.; Monedero, I.; León, C.; I. Guerrero, J.; Biscarri, J. and Millán, R. (2008). A DATA MINING METHOD BASED ON THE VARIABILITY OF THE CUSTOMER CONSUMPTION - A Special Application on Electric Utility Companies. In Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 6: ICEIS; ISBN 978-989-8111-37-1; ISSN 2184-4992, SciTePress, pages 370-374. DOI: 10.5220/0001721103700374

@conference{iceis08,
author={Félix Biscarri. and Ignacio Monedero. and Carlos León. and Juán {I. Guerrero}. and Jesús Biscarri. and Rocío Millán.},
title={A DATA MINING METHOD BASED ON THE VARIABILITY OF THE CUSTOMER CONSUMPTION - A Special Application on Electric Utility Companies},
booktitle={Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 6: ICEIS},
year={2008},
pages={370-374},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001721103700374},
isbn={978-989-8111-37-1},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 6: ICEIS
TI - A DATA MINING METHOD BASED ON THE VARIABILITY OF THE CUSTOMER CONSUMPTION - A Special Application on Electric Utility Companies
SN - 978-989-8111-37-1
IS - 2184-4992
AU - Biscarri, F.
AU - Monedero, I.
AU - León, C.
AU - I. Guerrero, J.
AU - Biscarri, J.
AU - Millán, R.
PY - 2008
SP - 370
EP - 374
DO - 10.5220/0001721103700374
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic