dc.creator | Guerrero Alonso, Juan Ignacio | es |
dc.creator | Parejo Matos, Antonio | es |
dc.creator | Personal Vázquez, Enrique | es |
dc.creator | Monedero Goicoechea, Iñigo Luis | es |
dc.creator | Biscarri Triviño, Félix | es |
dc.creator | Biscarri Triviño, Jesús | es |
dc.creator | León de Mora, Carlos | es |
dc.date.accessioned | 2021-10-20T11:02:35Z | |
dc.date.available | 2021-10-20T11:02:35Z | |
dc.date.issued | 2017 | |
dc.identifier.citation | Guerrero Alonso, J.I., Parejo Matos, A., Personal Vázquez, E., Monedero Goicoechea, I.L., Biscarri Triviño, F., Biscarri Triviño, J. y León de Mora, C. (2017). From Rule Based Expert System to High-Performance Data Analysis for Reduction of Non-Technical Losses on Power Grids. International Journal on Advances in Intelligent Systems, 10 (1-2), 136-146. | |
dc.identifier.issn | 1942-2679 | es |
dc.identifier.uri | https://hdl.handle.net/11441/126706 | |
dc.description.abstract | The Non-Technical Losses represent the non-billed
energy due to faults or illegal manipulations in customer
facilities. The objective of the Midas project is the detection of
Non-Technical Losses through the application of computational
intelligence over the information stored in utility company
databases. This project has several research lines, e.g., pattern
recognition, expert systems, big data and High Performance
Computing. This paper proposes a module which uses statistical
techniques to make patterns of correct consumption. The main
contribution of this module is the detection of cases, which are
usually classified as consumers with Non-Technical Loss
increasing the false positives and decreasing the total success
rate. This module is integrated with a rule based expert system
made up of other modules, such a text mining module and a data
warehousing module. The correct consumption patterns
(consumers without Non-Technical Losses) are generated using
rules, which will be used by a rule based expert system. Two
implementations are proposed. Both of them provided an
Intelligent Information System to reach unapproachable goals
for inspectors. Additionally, some highlighted cases of detected
patterns are described. | es |
dc.description.sponsorship | Ministerio de Economía y Competitividad TEC2013-40767-R | es |
dc.format | application/pdf | es |
dc.format.extent | 11 | es |
dc.language.iso | eng | es |
dc.publisher | IARIA | es |
dc.relation.ispartof | International Journal on Advances in Intelligent Systems, 10 (1-2), 136-146. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Non-technical losses | es |
dc.subject | Pattern recognition | es |
dc.subject | Expert system | es |
dc.subject | Big Data analytics | es |
dc.subject | High performance computing | es |
dc.subject | High performance data analysis | es |
dc.title | From Rule Based Expert System to High-Performance Data Analysis for Reduction of Non-Technical Losses on Power Grids | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Tecnología Electrónica | es |
dc.relation.projectID | TEC2013-40767-R | es |
dc.relation.publisherversion | http://www.iariajournals.org/intelligent_systems/tocv10n12.html | es |
dc.journaltitle | International Journal on Advances in Intelligent Systems | es |
dc.publication.volumen | 10 | es |
dc.publication.issue | 1-2 | es |
dc.publication.initialPage | 136 | es |
dc.publication.endPage | 146 | es |
dc.identifier.sisius | 21348144 | es |
dc.contributor.funder | Ministerio de Economía y Competitividad (MINECO). España | es |