(untitled) (Research, Society and Development, 2022)
This work proposes the use of the CNN-BLSTM neural network as a tool to predict the price of arabica coffee. The database provided by CEPEA (Center for Advanced Studies in Applied Economics) presents a historical series of the price of arabica coffee, in the period between January 1997 and December 2021. Forecast models based on neural networks LSTM, BLSTM, CNN and CNN-BLSTM were implemented, in the Python language, using the Keras framework. Results obtained, from the four models, were compared using MAE, RMSE and MAPE metrics. It was verified, for a horizon of 6 months, that the CNN-BLSTM model presented better performance.