dor_id: 4110271
506.#.#.a: Público
590.#.#.d: Los artículos enviados a la revista "Journal of Applied Research and Technology", se juzgan por medio de un proceso de revisión por pares
510.0.#.a: Scopus, Directory of Open Access Journals (DOAJ); Sistema Regional de Información en Línea para Revistas Científicas de América Latina, el Caribe, España y Portugal (Latindex); Indice de Revistas Latinoamericanas en Ciencias (Periódica); La Red de Revistas Científicas de América Latina y el Caribe, España y Portugal (Redalyc); Consejo Nacional de Ciencia y Tecnología (CONACyT); Google Scholar Citation
561.#.#.u: https://www.icat.unam.mx/
650.#.4.x: Ingenierías
336.#.#.b: article
336.#.#.3: Artículo de Investigación
336.#.#.a: Artículo
351.#.#.6: https://jart.icat.unam.mx/index.php/jart
351.#.#.b: Journal of Applied Research and Technology
351.#.#.a: Artículos
harvesting_group: RevistasUNAM
270.1.#.p: Revistas UNAM. Dirección General de Publicaciones y Fomento Editorial, UNAM en revistas@unam.mx
590.#.#.c: Open Journal Systems (OJS)
270.#.#.d: MX
270.1.#.d: México
590.#.#.b: Concentrador
883.#.#.u: https://revistas.unam.mx/catalogo/
883.#.#.a: Revistas UNAM
590.#.#.a: Coordinación de Difusión Cultural
883.#.#.1: https://www.publicaciones.unam.mx/
883.#.#.q: Dirección General de Publicaciones y Fomento Editorial
850.#.#.a: Universidad Nacional Autónoma de México
856.4.0.u: https://jart.icat.unam.mx/index.php/jart/article/view/1364/796
100.1.#.a: Valencia, Andrés M.; Caratar, Jesús; Caicedo, Gladys; Chamorro, Cristian
524.#.#.a: Valencia, Andrés M., et al. (2020). Proposal for a KDD-based procedure to obtain a set of intelligent systems training applied to the identification of failures in hydroelectric power plants. Journal of Applied Research and Technology; Vol. 18 Núm. 6, 2020; 376-389. Recuperado de https://repositorio.unam.mx/contenidos/4110271
245.1.0.a: Proposal for a KDD-based procedure to obtain a set of intelligent systems training applied to the identification of failures in hydroelectric power plants
502.#.#.c: Universidad Nacional Autónoma de México
561.1.#.a: Instituto de Ciencias Aplicadas y Tecnología, UNAM
264.#.0.c: 2020
264.#.1.c: 2020-12-31
653.#.#.a: knowledge discovery data; data mining; intelligent systems; failure diagnosis; training set; hydroelectric power plant
506.1.#.a: La titularidad de los derechos patrimoniales de esta obra pertenece a las instituciones editoras. Su uso se rige por una licencia Creative Commons BY-NC-SA 4.0 Internacional, https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.es, para un uso diferente consultar al responsable jurídico del repositorio por medio del correo electrónico gabriel.ascanio@icat.unam.mx
884.#.#.k: https://jart.icat.unam.mx/index.php/jart/article/view/1364
001.#.#.#: 074.oai:ojs2.localhost:article/1364
041.#.7.h: eng
520.3.#.a: This paper presents a procedure based on KDD (Knowledge Discovery Data), which allows the analysis of a data set to obtain structured information from the behavior of the system under specific conditions, such as system failure conditions at a hydroelectric power plant. By applying this procedure, the information obtained, it is structured in such a mode so that it can be used on the training of intelligent systems focused on fault diagnosis. The former procedure is necessary in the intelligent systems development stage because obtaining an effective training set requires extreme time and effort. The procedure was applied in the historical records of the Amaime hydroelectric power plant, located in Palmira, Valle del Cauca, Colombia, aiming to obtain patterns of behavior of the protection system which can be translated to different failures. This was possible by integrating a data mining technique such as hierarchical clustering and the statistical technique called the interpolation function. The main achievement of this work is to present a structured procedure that reduces the time to obtain a training set. In this specific case, the training set for mechanical failure of a hydroelectric power station was obtained, which can be used in the development of an intelligent system for failures diagnosis.
773.1.#.t: Journal of Applied Research and Technology; Vol. 18 Núm. 6 (2020); 376-389
773.1.#.o: https://jart.icat.unam.mx/index.php/jart
022.#.#.a: ISSN electrónico: 2448-6736; ISSN: 1665-6423
310.#.#.a: Bimestral
300.#.#.a: Páginas: 376-389
264.#.1.b: Instituto de Ciencias Aplicadas y Tecnología, UNAM
doi: https://doi.org/10.22201/icat.24486736e.2020.18.6.1364
harvesting_date: 2023-11-08 13:10:00.0
856.#.0.q: application/pdf
file_creation_date: 2020-12-17 21:40:04.0
file_modification_date: 2020-12-17 21:40:04.0
file_creator: Yolanda G.G.
file_name: 6c108f9f0ffc5171090878f8e8ef879001b3296cefeaab0b67eaaa937582d14f.pdf
file_pages_number: 14
file_format_version: application/pdf; version=1.7
file_size: 728684
last_modified: 2024-03-19 14:00:00
license_url: https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.es
license_type: by-nc-sa
No entro en nada
No entro en nada 2