Artificial Neural Network Modeling for Prediction of Dynamic Changes in Solution from Bioleaching by Indigenous Acidophilic Bacteria

Abstract

In this study, indigenous acidophilic bacteria living in mine drainage and hot acidic spring were collected and used for bioleaching experiments. The incubated indigenous acidophilic bacteria were inoculated on various minerals. The changes in pH, Eh, and heavy metal concentrations were examined with uninoculated controls to study bioleaching over time. As a result, the aspects of bioleaching varied greatly depending on the origin of microorganisms, the type of minerals, the temperature conditions, etc. We applied an ANN model to express and predict these complex bioleaching trends. Through the application of an ANN model, we developed the ANN models that can predict the changes in concentration of pH, Eh, and heavy metal ion concentrations and further evaluated predictability. Through this, the predictability of bioleaching using the ANN models can be confirmed. However, we also identified limitations, showing that further testing and application of the ANN models in more diverse experimental conditions are needed to improve the predictability of the ANN models.