Mineral Leaching Modeling Through Machine Learning Algorithms − A Review - Saldaña, Manuel; Neira, Purísima; Gallegos, Sandra; Salinas-Rodríguez, Eleazar; Pérez-Rey, Ignacio; Toro, Norman (Frontiers in Earth Science, 2022)
Artificial intelligence and machine learning algorithms have an increasingly pervasive presence in all fields of science due to their ability to find patterns, model dynamic systems and make predictions of complex processes. This review aims at providing to the researchers in the mineral processing area with structured knowledge about the applications of machine learning algorithms to the leaching process, showing the applications of techniques such as artificial neural networks (ANN), support vector machines (SVM) or Bayesian networks (BN), among others. Additionally, future perspectives are indicated, emphasizing both the generalization of the algorithms and the productive potential of the application of modeling, simulation and optimization of the tools studied here to industrial processes.