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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:

Efficient machine learning method for evaluating compressive strength of cement stabilized soft soil
Chen Zhang, Zhiduo Zhu, Fa Liu, et al.
Construction and Building Materials (2023) Vol. 392, pp. 131887-131887
Closed Access | Times Cited: 42

Showing 1-25 of 42 citing articles:

Machine learning-based prediction and experimental validation of heavy metal adsorption capacity of bentonite
Lisheng Guo, Xin Xu, Cencen Niu, et al.
The Science of The Total Environment (2024) Vol. 926, pp. 171986-171986
Closed Access | Times Cited: 21
Efficient prediction of California bearing ratio in solid waste-cement-stabilized soil using improved hybrid extreme gradient boosting model
Yiliang Tu, Qianglong Yao, Shuitao Gu, et al.
Materials Today Communications (2025) Vol. 43, pp. 111627-111627
Closed Access | Times Cited: 1
Prediction of maximum dynamic shear modulus of undisturbed marine soils in the eastern coast of China based on machine learning methods
Yiliang Tu, Qianglong Yao, Ying Zhou, et al.
Ocean Engineering (2025) Vol. 321, pp. 120382-120382
Closed Access | Times Cited: 1
Modeling Soil Behavior with Machine Learning: Static and Cyclic Properties of High Plasticity Clays Treated with Lime and Fly Ash
Gebrai̇l Bekdaş, Yaren Aydın, Sinan Melih Niğdeli, et al.
Buildings (2025) Vol. 15, Iss. 2, pp. 288-288
Open Access | Times Cited: 1
Predicting the crack repair rate of self-healing concrete using soft-computing tools
Yuanfeng Lou, Huiling Wang, Muhammad Nasir Amin, et al.
Materials Today Communications (2024) Vol. 38, pp. 108043-108043
Closed Access | Times Cited: 13
Compressive strength and sensitivity analysis of fly ash composite foam concrete: Efficient machine learning approach
Chen Zhang, Zhiduo Zhu, Liang Shi, et al.
Advances in Engineering Software (2024) Vol. 192, pp. 103634-103634
Closed Access | Times Cited: 10
Hybrid XGB model for predicting unconfined compressive strength of solid waste-cement-stabilized cohesive soil
Qianglong Yao, Yiliang Tu, Jiahui Yang, et al.
Construction and Building Materials (2024) Vol. 449, pp. 138242-138242
Closed Access | Times Cited: 9
Engineering properties and optimal design of foam lightweight soil composite fly ash: An eco-friendly subgrade material
Chen Zhang, Zhiduo Zhu, Yue Zhang, et al.
Journal of Cleaner Production (2023) Vol. 429, pp. 139631-139631
Closed Access | Times Cited: 18
Exploring Sustainable Solutions for Soil Stabilization through Explainable Gaussian Process-assisted Multi-Objective Optimization
Gautam, Kritesh Kumar Gupta, Debjit Bhowmik
Materials Today Communications (2024) Vol. 40, pp. 110154-110154
Closed Access | Times Cited: 5
Insights into the strength development in cement-treated soils: An explainable AI-based approach for optimized mix design
Muhammad Hasnain Ayub Khan, Adel Abdallah, Olivier Cuisinier
Computers and Geotechnics (2025) Vol. 180, pp. 107103-107103
Closed Access
Predicting the compressive strength of solid waste-cement stabilized compacted soil using machine learning model
Qianglong Yao, Yiliang Tu, Jiahui Yang
Materials Today Communications (2025), pp. 111882-111882
Closed Access
Utilizing construction and demolition waste in soft soil stabilization: A prediction model for enhanced strength and stiffness
Ecem Nur Barisoglu, Taher Ghalandari, D. Snoeck, et al.
Transportation Geotechnics (2025) Vol. 51, pp. 101530-101530
Closed Access
Comparing the performance of machine learning models for predicting the compressive strength of concrete
Arthur Afonso Bitencourt Loureiro, Ricardo Stefani
Deleted Journal (2024) Vol. 1, Iss. 1
Open Access | Times Cited: 4
Combined Correlation Analysis and Multilinear Regression for Strength Model of Cement-Stabilized Clayey Soils
Yalei Wu, Junjie Yang, X. Y. Liu, et al.
International Journal of Geomechanics (2024) Vol. 24, Iss. 9
Closed Access | Times Cited: 4
Compressive and tensile strength estimation of sustainable geopolymer concrete using contemporary boosting ensemble techniques
Ji Zhou, Qiong Tian, Ayaz Ahmad, et al.
REVIEWS ON ADVANCED MATERIALS SCIENCE (2024) Vol. 63, Iss. 1
Open Access | Times Cited: 3
Applicability and chemical mechanism of lightweight cement composite containing fly ash and sand for sustainable embankment
Chen Zhang, Yue Zhang, Zhiduo Zhu, et al.
Construction and Building Materials (2024) Vol. 443, pp. 137735-137735
Closed Access | Times Cited: 3
Explainable Artificial Intelligence for Predicting the Compressive Strength of Soil and Ground Granulated Blast Furnace Slag Mixtures
Ahmed Mohammed Awad Mohammed, Omayma Husain, Muyideen Abdulkareem, et al.
Results in Engineering (2024) Vol. 25, pp. 103637-103637
Open Access | Times Cited: 3
Prediction of the self-healing properties of concrete modified with bacteria and fibers using machine learning
Carolina Luiza Emerenciana Pessoa, Victor Hugo Peres Silva, Ricardo Stefani
Asian Journal of Civil Engineering (2023) Vol. 25, Iss. 2, pp. 1801-1810
Closed Access | Times Cited: 8
Machine learning for optimal ultra-fine cement plugging system in simulated high permeability sandstone reservoirs
H. Y. Wang, Yujia Hu, Tianbao Liu, et al.
Colloids and Surfaces A Physicochemical and Engineering Aspects (2024) Vol. 689, pp. 133753-133753
Closed Access | Times Cited: 2
Stacking Ensemble-Based Machine Learning Model for Predicting Deterioration Components of Steel W-Section Beams
Azadeh Khoshkroodi, Hossein Parvini Sani, Mojtaba Aajami
Buildings (2024) Vol. 14, Iss. 1, pp. 240-240
Open Access | Times Cited: 2
Experimenting the influence of corncob ash on the mechanical strength of slag-based geopolymer concrete
Jing Wang, Qian Qu, Suleman Ayub Khan, et al.
REVIEWS ON ADVANCED MATERIALS SCIENCE (2024) Vol. 63, Iss. 1
Open Access | Times Cited: 2
Supervised intelligent prediction of shear strength of rockfill materials based on data driven and a case study
Chuanqi Li, Jiamin Zhang, Xiancheng Mei, et al.
Transportation Geotechnics (2024) Vol. 45, pp. 101229-101229
Closed Access | Times Cited: 2
Modeling the strength parameters of agro waste-derived geopolymer concrete using advanced machine intelligence techniques
Ahmed A. Alawi Al-Naghi, Muhammad Nasir Amin, Suleman Ayub Khan, et al.
REVIEWS ON ADVANCED MATERIALS SCIENCE (2024) Vol. 63, Iss. 1
Open Access | Times Cited: 2
Intelligent mixture optimization for stabilized soil containing solid waste based on machine learning and evolutionary algorithms
Junzhi Wang, Geng Chen, Yonghui Chen, et al.
Construction and Building Materials (2024) Vol. 445, pp. 137794-137794
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
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