This investigation approaches the artificial neural networks applied to the ore drying process in carbonate-ammonia leaching.
To carry out this research, the main variables that characterize the process were identified. Besides, it was collected the data that
comprise a whole month of facility´s operation. Furthermore, it was developed a regression analysis backwards, step by step, which
allowed to determine that the linear correlation coefficient did not reach values higher than 0,62. In addition, it was pinpointed a
two layered feed - forward back propagation neural network to model the temperature. Thins one reached the correlation coefficient
values of 0,97 during its training and 0,95 in validation, as well as 0,87 in its generalization.
Keywords: Artificial Neuronal Network; Regression; Feed-Forward Backpropagation; Mineral Drying