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English Information

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Authors
# Name
1 Karla Ferreira(kferreira7581@gmail.com)
2 Alessandra Coelho(alessandra.coelho@ifsudestemg.edu.br)
3 João Lamas(joao.lamas@ifsudestemg.edu.br)

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Reference
# Reference
1 B3 - Bolsa Brasil Balcao (2024). Contratos futuros de boi gordo. http://www.b3.com.br/.
2 Bergmeir, C., Hyndman, R. J., and Benítez, J. M. (2016). Bagging exponential smoothing methods using stl decomposition and box–cox transformation. International Journal of Forecasting, 32(2):303–312.
3 Breiman, L. (2001). Random forests. Machine Learning, 45(1):5–32.
4 CEPEA/ESALQ-USP (2024). Centro de estudos avançados em economia aplicada. https://www.cepea.esalq.usp.br/.
5 Chen, T. and Guestrin, C. (2016). Xgboost: A scalable tree boosting system. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 785–794.
6 Drucker, H., Burges, C. J. C., Kaufman, L., Smola, A., and Vapnik, V. (1997). Support vector regression machines. Advances in Neural Information Processing Systems, 9.
7 Freitas, W. (2024). python-bcb: Python wrapper for brazilian central bank web services. https://github.com/wilsonfreitas/python-bcb.
8 Friedman, J. H. (2001). Greedy function approximation: A gradient boosting machine. The Annals of Statistics, 29(5):1189–1232.
9 Hochreiter, S. and Schmidhuber, J. (1997). Long short-term memory. Neural Computation, 9(8):1735–1780.
10 Kimball, R. and Ross, M. (2013). The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling. John Wiley & Sons.
11 Kontopoulou, V. I., Panagopoulos, A. D., Kakkos, I., and Matsopoulos, G. K. (2023). A review of arima vs. machine learning approaches for time series forecasting in data driven networks. Future Internet, 15(8).
12 Ministerio da Agricultura e Pecuária (2025). Estatísticas de comércio exterior do agronegócio brasileiro. https://www.gov.br/agricultura/.
13 Open-Meteo (2024). Open-meteo historical weather api. https://open-meteo.com/.
14 Reis Filho, I. J., Portari Junior, S. C., Oliveira, C. M., Barcelos, L. V., and Nunes Corrêa, G. (2021). A integração de séries temporais e dados de textos para a previsão de preços futuros de milho e soja. Revista de Sistemas de Informação, 1(1).
15 Tran, N.-Q., Felipe, A., Nguyen Ngoc, T., Huynh, T., Tran, Q., Tang, A., and Nguyen, T. (2023). Predicting agricultural commodities prices with machine learning: A review of current research. arXiv preprint arXiv:2310.18646.