Abstract
Contact and support
Need help, have a question, or want to contact the ResearchHub team?
© 2026 ResearchHub. Built for responsible scholarly connection.
Claudio Leiva, Diego Poblete, Claudio Acuña, María Astudillo
Abstract
Authors
Institutions
No local reference links have been materialized yet.
No local citing links have been materialized yet.
Estimation of copper grade, acid consumption, and moisture content in heap leaching using extended and unscented Kalman filters
10.3390/min15050521 · 2025
Experience on SX/EW pilot plant automation
10.1016/s1474-6670(17)37017-9 · 2000
Combining online process measurements and models to empirically test strategies for process monitoring
10.3182/20070821-3-ca-2919.00052 · 2007
Unresolved referenced work
Kept as external metadata until matched
Computer vision and image-based sensing in mine-to-plant operations and extractive metallurgy: a bibliometric and systematic literature review
10.1016/j.mineng.2026.110256 · 2026
Unresolved referenced work
Kept as external metadata until matched
Heap leaching. Computer simulation as an alternative technology
2015
Training feedforward networks with the Marquardt algorithm
10.1109/72.329697 · 1994
A simple and sensitive spectrophotometric method for the determination of copper(II) in aqueous solutions using a novel schiff base reagent
2024
Insight into the Bouguer-Beer-Lambert law: a review
Provenance
crossref
Confidence 100%
openalex
Confidence 95%
datacite
Confidence 0%
10.37256/sce.5220245325 · 2024
Single peak parameters technique for simultaneous measurements: Spectrophotometric sequential injection determination of Fe(II) and Fe(III)
10.1016/j.talanta.2015.06.040 · 2016
Potential copper production through 2035 in Chile
10.1007/s13563-020-00227-2 · 2020
Design of a sensor based on neural networks to determine sludge level of industrial thickeners
10.1177/1550147720933153 · 2020
Applying softcomputing for copper recovery in leaching process
2017
Optimization of mining–mineral processing integration using unsupervised machine learning algorithms
10.1007/s11053-020-09628-0 · 2020
Low-grade chalcopyrite ore, heap leaching or smelting recovery route?
10.1016/j.hydromet.2022.105885 · 2022
Enhancing comminution process modeling in mineral processing: a conjoint analysis approach for implementing neural networks with limited data
10.3390/mining4040054 · 2024
Spectrophotometric determination of copper (Ii) in soil from ahero rice irrigation schemes using hydroxytriazene
2020
10.1117/1.jbo.26.10.100901
10.1117/1.jbo.26.10.100901
10.1016/b978-0-443-40294-4.00029-3
10.1016/b978-0-443-40294-4.00029-3
Hollow drop bubbles: a preliminary study of simplified prototype for improving copper(II) extraction with ACORGA® M5640 using coated bubble swarm
10.1016/j.hydromet.2024.106340 · 2024
Unresolved referenced work
Kept as external metadata until matched
Colorimetric measurement of copper(II) in sand using direct electrokinetic extraction into a polymer inclusion membrane
10.1016/j.aca.2025.344262 · 2025
Unresolved referenced work
Kept as external metadata until matched
A brief note on the heap leaching technologies for the recovery of valuable metals
10.3390/su11123347 · 2019
Unresolved referenced work
Kept as external metadata until matched
Threshold concentration in the nonlinear absorbance law †
10.1039/c7cp01514c · 2017
Unresolved referenced work
Kept as external metadata until matched
The evaluation of grinding process using artificial neural network
10.1016/j.minpro.2015.11.013 · 2016
Correlation and prediction of saline solution properties for their use in mineral processing using artificial neural networks
10.2166/wrd.2015.132 · 2015
Unresolved referenced work
Kept as external metadata until matched
Correlation and prediction of saline solution properties for their use in mineral processing using artificial neural networks
10.2166/wrd.2015.132 · doi-reference
The evaluation of grinding process using artificial neural network
10.1016/j.minpro.2015.11.013 · doi-reference
Threshold concentration in the nonlinear absorbance law †
10.1039/c7cp01514c · doi-reference
A brief note on the heap leaching technologies for the recovery of valuable metals
10.3390/su11123347 · doi-reference
Colorimetric measurement of copper(II) in sand using direct electrokinetic extraction into a polymer inclusion membrane
10.1016/j.aca.2025.344262 · doi-reference
Hollow drop bubbles: a preliminary study of simplified prototype for improving copper(II) extraction with ACORGA® M5640 using coated bubble swarm
10.1016/j.hydromet.2024.106340 · doi-reference
10.1016/b978-0-443-40294-4.00029-3
10.1016/b978-0-443-40294-4.00029-3 · doi-reference
10.1117/1.jbo.26.10.100901
10.1117/1.jbo.26.10.100901 · doi-reference
Enhancing comminution process modeling in mineral processing: a conjoint analysis approach for implementing neural networks with limited data
10.3390/mining4040054 · doi-reference
Low-grade chalcopyrite ore, heap leaching or smelting recovery route?
10.1016/j.hydromet.2022.105885 · doi-reference
Optimization of mining–mineral processing integration using unsupervised machine learning algorithms
10.1007/s11053-020-09628-0 · doi-reference
Design of a sensor based on neural networks to determine sludge level of industrial thickeners
10.1177/1550147720933153 · doi-reference
Potential copper production through 2035 in Chile
10.1007/s13563-020-00227-2 · doi-reference
Single peak parameters technique for simultaneous measurements: Spectrophotometric sequential injection determination of Fe(II) and Fe(III)
10.1016/j.talanta.2015.06.040 · doi-reference
Insight into the Bouguer-Beer-Lambert law: a review
10.37256/sce.5220245325 · doi-reference
Training feedforward networks with the Marquardt algorithm
10.1109/72.329697 · doi-reference
Computer vision and image-based sensing in mine-to-plant operations and extractive metallurgy: a bibliometric and systematic literature review
10.1016/j.mineng.2026.110256 · doi-reference
Combining online process measurements and models to empirically test strategies for process monitoring
10.3182/20070821-3-ca-2919.00052 · doi-reference
Experience on SX/EW pilot plant automation
10.1016/s1474-6670(17)37017-9 · doi-reference
Estimation of copper grade, acid consumption, and moisture content in heap leaching using extended and unscented Kalman filters
10.3390/min15050521 · doi-reference