Analysis of judiciary expenditure and productivity using machine learning techniques (2023)
Fonte: Mathematics. Unidades: FEA, ESALQ
Assuntos: APRENDIZADO COMPUTACIONAL, DESPESAS PROCESSUAIS, PRODUTIVIDADE, REDES NEURAIS, SISTEMA JUDICIÁRIO
ABNT
VASCONCELOS, Fernando Freire et al. Analysis of judiciary expenditure and productivity using machine learning techniques. Mathematics, v. 11, p. 1-19, 2023Tradução . . Disponível em: https://doi.org/10.3390/math11143195. Acesso em: 24 ago. 2024.APA
Vasconcelos, F. F., Sátiro, R. M., Fávero, L. P. L., Bortoloto, G. T., & Corrêa, H. L. (2023). Analysis of judiciary expenditure and productivity using machine learning techniques. Mathematics, 11, 1-19. doi:10.3390/math11143195NLM
Vasconcelos FF, Sátiro RM, Fávero LPL, Bortoloto GT, Corrêa HL. Analysis of judiciary expenditure and productivity using machine learning techniques [Internet]. Mathematics. 2023 ; 11 1-19.[citado 2024 ago. 24 ] Available from: https://doi.org/10.3390/math11143195Vancouver
Vasconcelos FF, Sátiro RM, Fávero LPL, Bortoloto GT, Corrêa HL. Analysis of judiciary expenditure and productivity using machine learning techniques [Internet]. Mathematics. 2023 ; 11 1-19.[citado 2024 ago. 24 ] Available from: https://doi.org/10.3390/math11143195