Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Marta Galende"'
Publikováno v:
IEEE Access, Vol 11, Pp 26611-26623 (2023)
Decentralized monitoring methods, which divide the process variables into several blocks and perform local monitoring for each sub-block, have been gaining increasing attention in large-scale plant-wide monitoring due to the complexity of their proce
Externí odkaz:
https://doaj.org/article/b53ce1d9192e4eb79efd1e0e8c8dac93
Autor:
Anibal Reñones, Marta Galende
Publikováno v:
Advances in Distributed Computing and Artificial Intelligence Journal, Vol 9, Iss 4, Pp 83-94 (2020)
Practical research in AI often lacks of available and reliable datasets so the practitioners can try different algorithms. The field of predictive maintenance is particularly challenging in this aspect as many researchers don't have access to full-si
Externí odkaz:
https://doaj.org/article/74d868ec38fc4650ae04cff4a9c54a39
Autor:
Marta Galende, Aníbal Renõnes
Publikováno v:
Proceedings of the V Workshop on Disruptive Information and Communication Technologies for Innovation and Digital Transformation.
Publikováno v:
Proceedings of the V Workshop on Disruptive Information and Communication Technologies for Innovation and Digital Transformation.
Autor:
Marta Galende, Anibal Reñones
Publikováno v:
Advances in Distributed Computing and Artificial Intelligence Journal, Vol 9, Iss 4, Pp 83-94 (2020)
Practical research in AI often lacks of available and reliable datasets so the practitioners can try different algorithms. The field of predictive maintenance is particularly challenging in this aspect as many researchers don't have access to full-si
Autor:
Marta Galende, Christoph Bergmeir, Carlos Martinez Bertrand, Daniel Peralta, Frank Klawonn, G.I. Sainz-Palmero, Martin Krone, José Manuel Benítez, Manuel Menéndez
Publikováno v:
JOURNAL OF COMPUTING IN CIVIL ENGINEERING
Railway track maintenance is a critical problem for any railway administrator. More precisely, preventive maintenance scheduling is a nondeterministic polynomial time (NP)–hard problem, whi...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0e04ab1b5c18e6707cb194e13bda840c
https://biblio.ugent.be/publication/8565703
https://biblio.ugent.be/publication/8565703
Autor:
Gregorio Sainz Palmero, Jose M, Alberto Moral, Jorge Rodríguez, Laura Pablos, Ruben Carnerero, Manuel Parra, Francisco Campo, Marta Galende
Publikováno v:
Fifth International Conference on Advances in Civil, Structural and Mechanical Engineering - CSM 2017.
Publikováno v:
Information Sciences. 276:63-79
In this contribution, we propose a two-stage method for Accurate Fuzzy Modeling in High-Dimensional Regression Problems using Approximate Takagi-Sugeno-Kang Fuzzy Rule-Based Systems. In the first stage, an evolutionary data base learning is performed