Application of Artificial Neural Networks to Predict Pressure Oxidative Leaching of Molybdenite Concentrate in Nitric Acid Media

Abstract

This study is concerned with investigation of pressure oxidative leaching of entire molybdenum of a molybdenite concentrate. Effects of oxygen pressure, stirring speed, pulp density, acid concentration, and temperature on the leaching rate of molybdenum were studied. A three-layer feed-forward artificial neural network was applied to model the effect of the abovementioned parameters on the leaching ability. The leaching efficiency was considered as a target value for modeling. The quantified leaching efficiencies obtained by applying different parameters demonstrated a good agreement with neural network predictions.