Source: Measurement. Unidade: EESC
Subjects: APRENDIZADO COMPUTACIONAL, REDES DE DISTRIBUIÇÃO DE ENERGIA ELÉTRICA, ANÁLISE DE ONDALETAS
ABNT
CAOBIANCO, Luiz Gustavo e GUIDO, Rodrigo Capobianco e SILVA, Ivan Nunes da. Wavelet-based features selected with Paraconsistent Feature Engineering successfully classify events in low-voltage grids. Measurement, v. 170, 2021Tradução . . Disponível em: http://dx.doi.org/10.1016/j.measurement.2020.108711. Acesso em: 08 out. 2024.APA
Caobianco, L. G., Guido, R. C., & Silva, I. N. da. (2021). Wavelet-based features selected with Paraconsistent Feature Engineering successfully classify events in low-voltage grids. Measurement, 170. doi:10.1016/j.measurement.2020.108711NLM
Caobianco LG, Guido RC, Silva IN da. Wavelet-based features selected with Paraconsistent Feature Engineering successfully classify events in low-voltage grids [Internet]. Measurement. 2021 ; 170[citado 2024 out. 08 ] Available from: http://dx.doi.org/10.1016/j.measurement.2020.108711Vancouver
Caobianco LG, Guido RC, Silva IN da. Wavelet-based features selected with Paraconsistent Feature Engineering successfully classify events in low-voltage grids [Internet]. Measurement. 2021 ; 170[citado 2024 out. 08 ] Available from: http://dx.doi.org/10.1016/j.measurement.2020.108711