Applying Softcomputing for Copper Recovery in Leaching Process. - Claudio Leiva; Víctor Flores; Felipe Salgado; Diego Poblete; Claudio Acuña (Sci. Program., 2017)

Design of a sensor based on neural networks to determine sludge level of industrial thickeners. - Mauricio A. Leiva; Claudio Acuña; Claudio Leiva (Int. J. Distributed Sens. Networks, 2020)

Using Artificial Intelligence Techniques to Improve the Prediction of Copper Recovery by Leaching. - Víctor Flores; Brian Keith; Claudio Leiva (J. Sensors, 2020)

A Computer Simulator Model for Generating Sulphuric Acid and Improve the Operational Results, Using Operational Data from a Chemical Plant. - Claudio Leiva; Víctor Flores; Carolina Aguilar (J. Sensors, 2020)

Characterization of Filamentous Flocs to Predict Sedimentation Parameters Using Image Analysis. - M. A. Molina; Claudio Abraham Acuña Pérez; Claudio Leiva (J. Sensors, 2020)

Flow Enhancement of Mineral Pastes to Increase Water Recovery in Tailings: A Matlab-Based Imaging Processing Tool. - Sofía L. Mondaca; Claudio Leiva; Claudio A. Acuña; Eduardo A. Serey (Sci. Program., 2020)

A Comparative Study on Supervised Machine Learning Algorithms for Copper Recovery Quality Prediction in a Leaching Process. - Víctor Flores; Claudio Leiva (Sensors, 2021)