Correlation and Prediction of the Solubility of Air Gases in Saline Solutions for Mining Processes, Using Artificial Neural Networks

Abstract

Artificial neural networks (ANN) are used to correlate and predict the solubility of air gases (oxygen, nitrogen, and argon) in saline solutions. Several network architectures were considered in the study and correlated and predicted values of solubility were compared with values obtained from the literature. The model is general in the sense that just one model can correlate and predict the solubility of any of the three gases. As a measure of the accuracy of the method, the average relative deviation, the average relative absolute deviation, and the maximum relative absolute deviation are evaluated. The ANN model obtained give lower deviations than analytical models presented in the literature. The chosen ANN model give absolute deviations lower than 1% with some few exceptions and maximum relative absolute deviations are always below 6%.