Source: Electric Power Systems Research. Unidade: EESC
Subjects: INTELIGÊNCIA ARTIFICIAL, PROCESSAMENTO DE SINAIS, CONVERSORES ELÉTRICOS, ENGENHARIA ELÉTRICA
ABNT
DAVI, Moisés Junior Batista Borges e OLESKOVICZ, Mario e LOPES, Felipe V. Exploring the potential of a machine learning-based methodology for fault classification in inverter-based resource interconnection lines. Electric Power Systems Research, v. 223, p. 1-9, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.epsr.2023.109532. Acesso em: 29 ago. 2024.APA
Davi, M. J. B. B., Oleskovicz, M., & Lopes, F. V. (2023). Exploring the potential of a machine learning-based methodology for fault classification in inverter-based resource interconnection lines. Electric Power Systems Research, 223, 1-9. doi:10.1016/j.epsr.2023.109532NLM
Davi MJBB, Oleskovicz M, Lopes FV. Exploring the potential of a machine learning-based methodology for fault classification in inverter-based resource interconnection lines [Internet]. Electric Power Systems Research. 2023 ; 223 1-9.[citado 2024 ago. 29 ] Available from: https://doi.org/10.1016/j.epsr.2023.109532Vancouver
Davi MJBB, Oleskovicz M, Lopes FV. Exploring the potential of a machine learning-based methodology for fault classification in inverter-based resource interconnection lines [Internet]. Electric Power Systems Research. 2023 ; 223 1-9.[citado 2024 ago. 29 ] Available from: https://doi.org/10.1016/j.epsr.2023.109532