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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Optimization of the SAG Grinding Process Using Statistical Analysis and Machine Learning: A Case Study of the Chilean Copper Mining Industry
Manuel Saldaña, Edelmira D. Gálvez, Alessandro Navarra, et al.
Materials (2023) Vol. 16, Iss. 8, pp. 3220-3220
Open Access | Times Cited: 9

Showing 9 citing articles:

The future of the mining industry with artificial intelligence
Walid K. Hasan, Mohammad Al-Fawa’reh, Matt Madelatparvar, et al.
Elsevier eBooks (2025), pp. 383-407
Closed Access
Machine Learning in Latin America
Jorge Ignacio Anguiano Lizaola, Miguel Delgado-Prieto, A. García, et al.
IGI Global eBooks (2025), pp. 317-346
Closed Access
Development MPC for the Grinding Process in SAG Mills Using DEM Investigations on Liner Wear
И. И. Белоглазов, Vyacheslav Plaschinsky
Materials (2024) Vol. 17, Iss. 4, pp. 795-795
Open Access | Times Cited: 3
Stability Assessment of an Ore Mill Electric Drive Using Machine Learning
Marinka K. Baghdasaryan, Vardan Hovhannisyn
HighTech and Innovation Journal (2024) Vol. 5, Iss. 2, pp. 213-230
Open Access | Times Cited: 3
Effect of Size-Distribution Environment on Breakage Parameters Using Closed-Cycle Grinding Tests
Evangelos Petrakis
Materials (2023) Vol. 16, Iss. 24, pp. 7687-7687
Open Access | Times Cited: 3
Machine Learning Algorithms for Semi-Autogenous Grinding Mill Operational Regions’ Identification
Pedro Lopez, I. Reyes, Nathalie Risso, et al.
Minerals (2023) Vol. 13, Iss. 11, pp. 1360-1360
Open Access | Times Cited: 2
Prediction of energy consumption in grinding using artificial neural networks to improve the distribution of fragmentation size [Predicción del consumo de energía en la molienda utilizando redes neuronales artificiales para mejorar la distribución del tamaño de la fragmentación]
Jaime Yoni Anticona Cueva, Jhon Vera Encarnación, Tomas Jubencio Anticona Cueva, et al.
Journal of Energy & Environmental Sciences (2024) Vol. 8, Iss. 1, pp. 1-13
Open Access
Investigating Dynamic Behavior in SAG Mill Pebble Recycling Circuits: A Simulation Approach
Haijie Li, Gauti Asbjörnsson, Kanishk Bhadani, et al.
Minerals (2024) Vol. 14, Iss. 7, pp. 716-716
Open Access
Dynamic system employed for predicting noise emission at new constructed mineral ore processing plant
Edi Karyono Putro, Nieke Karnaningroem, Arie Dipareza Syafei
Noise Mapping (2023) Vol. 10, Iss. 1
Open Access
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