Zobrazeno 1 - 10
of 93
pro vyhledávání: '"Jose Sepulveda"'
Publikováno v:
Applied Sciences, Vol 11, Iss 16, p 7523 (2021)
The goal of this paper is to develop, implement, and validate a methodology for wind turbines’ main bearing fault prediction based on an ensemble of an artificial neural network (normality model designed at turbine level) and an isolation forest (a
Externí odkaz:
https://doaj.org/article/1dc94ad0774b463f9d0077cd6e6d5923
Publikováno v:
Sensors, Vol 21, Iss 4, p 1512 (2021)
A novel and innovative solution addressing wind turbines’ main bearing failure predictions using SCADA data is presented. This methodology enables to cut setup times and has more flexible requirements when compared to the current predictive algorit
Externí odkaz:
https://doaj.org/article/9e8412ce6cbd489b8d864331354a65fb
Autor:
Alejandra Quintanar Isaías, Alma Montero Alarcón, Daniel Ramírez Miranda, José Luis Criales Cortés, José Luis Ruvalcaba Sil, José Sepúlveda Sánchez, Judith Katia Perdigón Castañeda, María Eugenia Marín Benito, Mayra Dafne Manrique Ortega, Pablo Francisco Amador Marrero, Sor Beatriz Alceda, Valentina Aguilar Melo
El patrimonio escultórico de tipo religioso en México es vasto en su diseño, historia, usos y las costumbres que de ellos emanan. Este libro muestra esos preceptos en la labor ocurrida en el convento concepcionista del Dulce Nombre de María y San
Akademický článek
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Autor:
Portalés, Ignacio Pareja, Palma, Daniela Hurtado, Ezquerro, Ángela Gago, Gisbert, María José Sepúlveda, Benet, Mercedes Fernández, Pérez, Cristina Navarro, García, Fernando Martínez, Sala, Enrique Rodilla
Publikováno v:
In Revista clinica espanola November 2023 223 Supplement 2:S1029-S1031
Publikováno v:
Archives of Computational Methods in Engineering. 29:4683-4733
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a75577f5444dea902b2cadd014943138
https://doi.org/10.1007/s11831-022-09760-5
https://doi.org/10.1007/s11831-022-09760-5
Publikováno v:
Applied Sciences, Vol 11, Iss 7523, p 7523 (2021)
Applied Sciences
Volume 11
Issue 16
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Applied Sciences
Volume 11
Issue 16
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
The goal of this paper is to develop, implement, and validate a methodology for wind turbines’ main bearing fault prediction based on an ensemble of an artificial neural network (normality model designed at turbine level) and an isolation forest (a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e969436fa75fa9d1c2894cc68d5ce240
https://www.mdpi.com/2076-3417/11/16/7523
https://www.mdpi.com/2076-3417/11/16/7523
Akademický článek
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Publikováno v:
Goldschmidt Abstracts.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8e0de2b979719ae03544ba63bd401221
https://doi.org/10.46427/gold2020.1140
https://doi.org/10.46427/gold2020.1140
Autor:
Jiuwen Cao, Shuya Ding, Zhiping Lin, Jose Sepulveda, Bilal Mirza, Xiaoping Lai, Tam V. Nguyen
Publikováno v:
Neurocomputing. 277:139-148
In this paper, we propose a weighted online sequential extreme learning machine with kernels (WOS-ELMK) for class imbalance learning (CIL). The existing online sequential extreme learning machine (OS-ELM) methods for CIL use random feature mapping. W
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ecab6d27b3bee8ce07f81124bb998787
https://doi.org/10.1016/j.neucom.2017.02.102
https://doi.org/10.1016/j.neucom.2017.02.102