Source: Expert Systems with Applications. Unidade: EP
Assunto: APRENDIZADO COMPUTACIONAL
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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: 08 nov. 2025.APA
Felizardo, L. K., Brandimarte, P., Del Moral Hernandez, E., Reali Costa, A. H., 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, Reali Costa AH, 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 2025 nov. 08 ] Available from: https://doi.org/10.1016/j.eswa.2022.117259Vancouver
Felizardo LK, Brandimarte P, Del Moral Hernandez E, Reali Costa AH, 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 2025 nov. 08 ] Available from: https://doi.org/10.1016/j.eswa.2022.117259
