Source: Expert Systems with Applications. Unidade: EP
Assunto: APRENDIZADO COMPUTACIONAL
ABNT
FELIZARDO, Leonardo Kanashiro et al. Outperforming algorithmic trading reinforcement learning systems: a supervised approach to the cryptocurrency market. Expert Systems with Applications, v. 202, p. 1-13, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.eswa.2022.117259. Acesso em: 17 out. 2024.APA
Felizardo, L. K., Brandimarte, P., Del Moral Hernandez, E., Costa, A. H. R., Matsumoto, E. Y., Paiva, F. C. L., & Graves, C. de V. (2022). Outperforming algorithmic trading reinforcement learning systems: a supervised approach to the cryptocurrency market. Expert Systems with Applications, 202, 1-13. doi:10.1016/j.eswa.2022.117259NLM
Felizardo LK, Brandimarte P, Del Moral Hernandez E, Costa AHR, Matsumoto EY, Paiva FCL, Graves C de V. Outperforming algorithmic trading reinforcement learning systems: a supervised approach to the cryptocurrency market [Internet]. Expert Systems with Applications. 2022 ; 202 1-13.[citado 2024 out. 17 ] Available from: https://doi.org/10.1016/j.eswa.2022.117259Vancouver
Felizardo LK, Brandimarte P, Del Moral Hernandez E, Costa AHR, Matsumoto EY, Paiva FCL, Graves C de V. Outperforming algorithmic trading reinforcement learning systems: a supervised approach to the cryptocurrency market [Internet]. Expert Systems with Applications. 2022 ; 202 1-13.[citado 2024 out. 17 ] Available from: https://doi.org/10.1016/j.eswa.2022.117259