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pro vyhledávání: '"R, Martín"'
As a technique that can compactly represent complex patterns, machine learning has significant potential for predictive inference. K-fold cross-validation (CV) is the most common approach to ascertaining the likelihood that a machine learning outcome
Externí odkaz:
http://arxiv.org/abs/2401.16407
Autor:
R. Basili, L. Danciu, C. Beauval, K. Sesetyan, S. P. Vilanova, S. Adamia, P. Arroucau, J. Atanackov, S. Baize, C. Canora, R. Caputo, M. M. C. Carafa, E. M. Cushing, S. Custódio, M. B. Demircioglu Tumsa, J. C. Duarte, A. Ganas, J. García-Mayordomo, L. Gómez de la Peña, E. Gràcia, P. Jamšek Rupnik, H. Jomard, V. Kastelic, F. E. Maesano, R. Martín-Banda, S. Martínez-Loriente, M. Neres, H. Perea, B. Šket Motnikar, M. M. Tiberti, N. Tsereteli, V. Tsironi, R. Vallone, K. Vanneste, P. Zupančič, D. Giardini
Publikováno v:
Natural Hazards and Earth System Sciences, Vol 24, Pp 3945-3976 (2024)
Earthquake hazard analyses rely on seismogenic source models. These are designed in various fashions, such as point sources or area sources, but the most effective is the three-dimensional representation of geological faults. We here refer to such mo
Externí odkaz:
https://doaj.org/article/96f6bdd7b25c49699d6fe11b661f7f09
Autor:
Sandra Fuentes, Duxan Arancibia, Marcelo Rojas, Francisca Carmona, Andrea Ortega, Julio Valenzuela, Christian Hernández-Álvarez, Inocencio R. Martín
Publikováno v:
ACS Omega, Vol 9, Iss 26, Pp 28061-28071 (2024)
Externí odkaz:
https://doaj.org/article/1acdee1e7a8041fb812df92891276e0c
Autor:
Ivana K. Levy, Débora Salustro, Fernando Battaglini, Leonardo Lizarraga, Daniel H. Murgida, Rosalía Agusti, Norma D’Accorso, Dorotea Raventos Segura, Lorena González Palmén, R. Martín Negri
Publikováno v:
ACS Omega, Vol 9, Iss 9, Pp 10445-10458 (2024)
Externí odkaz:
https://doaj.org/article/8b5dabf9545c491099974e826372cb19
Autor:
P. Gómez-Porro, B. Cabal-Paz, S. Valenzuela-Chamorro, Z. Desanvicente-Celis, J. Sabin-Muñoz, C. Ochoa-López, C. Flórez, S. Enríquez-Calzada, R. Martín-García, Í. Esain-González, B. García-Fleitas, L. Silva-Hernández, Á. Ruiz-Molina, E. Gamo-González, A. Durán-Lozano, R. Velasco-Calvo, L. Alba-Alcántara, R. González-Santiago, A. Callejas-Díaz, B. Brea-Álvarez, J.-C. Salazar-Uribe, C. Escamilla-Crespo, J. Carneado-Ruiz
Publikováno v:
Neurología (English Edition), Vol 39, Iss 1, Pp 43-54 (2024)
Background: Ischaemic stroke may be a major complication of SARS-CoV-2 infection. Studying and characterising the different aetiological subtypes, clinical characteristics, and functional outcomes may be valuable in guiding patient selection for opti
Externí odkaz:
https://doaj.org/article/60b1c8220aee43f6a45e16f0e5ca355e
Publikováno v:
In Applied Acoustics 5 July 2024 223
Autor:
S. Cioni, F. Papi, L. Pagamonci, A. Bianchini, N. Ramos-García, G. Pirrung, R. Corniglion, A. Lovera, J. Galván, R. Boisard, A. Fontanella, P. Schito, A. Zasso, M. Belloli, A. Sanvito, G. Persico, L. Zhang, Y. Li, Y. Zhou, S. Mancini, K. Boorsma, R. Amaral, A. Viré, C. W. Schulz, S. Netzband, R. Soto-Valle, D. Marten, R. Martín-San-Román, P. Trubat, C. Molins, R. Bergua, E. Branlard, J. Jonkman, A. Robertson
Publikováno v:
Wind Energy Science, Vol 8, Pp 1659-1691 (2023)
This study reports the results of the second round of analyses of the Offshore Code Comparison, Collaboration, Continued, with Correlation and unCertainty (OC6) project Phase III. While the first round investigated rotor aerodynamic loading, here, fo
Externí odkaz:
https://doaj.org/article/326f4baa5854447b8a8ee0243049911c
Publikováno v:
Wind Energy Science, Vol 8, Pp 1597-1611 (2023)
The numerical study of floating offshore wind turbines (FOWTs) requires accurate integrated simulations which consider the aerodynamic, hydrodynamic, servo and elastic responses of these systems. In addition, the floating system dynamics couplings ne
Externí odkaz:
https://doaj.org/article/48562945e77f4f88b035fb7843a7770a
Publikováno v:
Neurología, Vol 38, Iss 8, Pp 577-590 (2023)
Resumen: Introducción: La aplicación de la inteligencia artificial y en particular de algoritmos de aprendizaje automático o «machine learning» (ML) constituye un desafío y al mismo tiempo una gran oportunidad en diversas disciplinas científic
Externí odkaz:
https://doaj.org/article/989a7f075f2846deb3f1f4a3e26489bf
Autor:
Terry Flew, Fiona R. Martin
This Open Access volume provides an in-depth exploration of global policy and governance issues related to digital platform regulation. With an international ensemble of contributors, the volume has at its heard the question: what would actually be i