Improving current forecast by leveraging measured data and numerical models via LiESNs (2025)
Fonte: Environmental Modelling and Software. Unidades: EP, IO
Assuntos: APRENDIZADO COMPUTACIONAL, REDES NEURAIS, PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS)
ABNT
MORENO, Felipe Marino et al. Improving current forecast by leveraging measured data and numerical models via LiESNs. Environmental Modelling and Software, v. 192, p. 1-13, 2025Tradução . . Disponível em: https://doi.org/10.1016/j.envsoft.2025.106556. Acesso em: 08 out. 2025.APA
Moreno, F. M., Barros, M. R. de, Correia, A. J. L., Mathias, M. S., Dottori, M., Reali Costa, A. H., et al. (2025). Improving current forecast by leveraging measured data and numerical models via LiESNs. Environmental Modelling and Software, 192, 1-13. doi:10.1016/j.envsoft.2025.106556NLM
Moreno FM, Barros MR de, Correia AJL, Mathias MS, Dottori M, Reali Costa AH, Gomi ES, Cozman FG, Tannuri EA. Improving current forecast by leveraging measured data and numerical models via LiESNs [Internet]. Environmental Modelling and Software. 2025 ; 192 1-13.[citado 2025 out. 08 ] Available from: https://doi.org/10.1016/j.envsoft.2025.106556Vancouver
Moreno FM, Barros MR de, Correia AJL, Mathias MS, Dottori M, Reali Costa AH, Gomi ES, Cozman FG, Tannuri EA. Improving current forecast by leveraging measured data and numerical models via LiESNs [Internet]. Environmental Modelling and Software. 2025 ; 192 1-13.[citado 2025 out. 08 ] Available from: https://doi.org/10.1016/j.envsoft.2025.106556