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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:

Weighted ensembles of artificial neural networks based on Gaussian mixture modeling for truck productivity prediction at open-pit mines
Chengkai Fan, Na Zhang, Bei Jiang, et al.
Mining Metallurgy & Exploration (2023) Vol. 40, Iss. 2, pp. 583-598
Closed Access | Times Cited: 9

Showing 9 citing articles:

Forecasting unconfined compressive strength of calcium sulfoaluminate cement mixtures using ensemble machine learning techniques integrated with shapely-additive explanations
Chathuranga Balasooriya Arachchilage, Guangping Huang, Chengkai Fan, et al.
Construction and Building Materials (2023) Vol. 409, pp. 134083-134083
Closed Access | Times Cited: 13
Using deep neural networks coupled with principal component analysis for ore production forecasting at open-pit mines
Chengkai Fan, Na Zhang, Bei Jiang, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2023) Vol. 16, Iss. 3, pp. 727-740
Open Access | Times Cited: 10
Combinatorial machine learning approaches for high-rise building cost prediction and their interpretability analysis
Zenghui Liu, Jing Lin
Journal of Asian Architecture and Building Engineering (2024), pp. 1-12
Open Access | Times Cited: 3
Deep Neural Network Models for Improving Truck Productivity Prediction in Open-pit Mines
Ömer Faruk Uğurlu, Chengkai Fan, Bei Jiang, et al.
Mining Metallurgy & Exploration (2024) Vol. 41, Iss. 2, pp. 619-636
Closed Access | Times Cited: 2
Machine learning with SHapley additive exPlanations for evaluating mine truck productivity under real-site weather conditions at varying temporal resolutions
Chengkai Fan, Chathuranga Balasooriya Arachchilage, Na Zhang, et al.
International Journal of Mining Reclamation and Environment (2024) Vol. 38, Iss. 10, pp. 810-832
Closed Access | Times Cited: 2
Hybrid extreme gradient boosting regressor models for the multi-objective mixture design optimization of cementitious mixtures incorporating mine tailings as fine aggregates
Chathuranga Balasooriya Arachchilage, Guangping Huang, Jian Zhao, et al.
Cement and Concrete Composites (2024), pp. 105787-105787
Open Access | Times Cited: 2
Machine learning for open-pit mining: a systematic review
Shi Qiang Liu, Lizhu Liu, Erhan Kozan, et al.
International Journal of Mining Reclamation and Environment (2024), pp. 1-39
Closed Access | Times Cited: 1
Machine learning-assisted characterization of the thermal conductivity of cement-based grouts for borehole heat exchangers
Jian Zhao, Chengkai Fan, Guangping Huang, et al.
Construction and Building Materials (2024) Vol. 449, pp. 138506-138506
Open Access | Times Cited: 1
Knowledge-informed Variational Bayesian Gaussian mixture regression model for predicting mixed oil length
Ziyun Yuan, Lei Chen, Gang Liu, et al.
Energy (2023) Vol. 285, pp. 129248-129248
Closed Access | Times Cited: 3
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