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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.

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Showing 18 citing articles:

A critical review on modeling and prediction on properties of fresh and hardened geopolymer composites
Peng Zhang, Yifan Mao, Weisuo Yuan, et al.
Journal of Building Engineering (2024) Vol. 88, pp. 109184-109184
Closed Access | Times Cited: 22
Prediction of mechanical properties of high‐performance concrete and ultrahigh‐performance concrete using soft computing techniques: A critical review
Rakesh Kumar, Baboo Rai, Pijush Samui
Structural Concrete (2024)
Closed Access | Times Cited: 16
Explainable AutoML models for predicting the strength of high-performance concrete using Optuna, SHAP and ensemble learning
Muhammad Salman Khan, Tianbo Peng, Muhammad Adeel Khan, et al.
Frontiers in Materials (2025) Vol. 12
Open Access
Innovative use of corncob ash in concrete: a machine learning perspective on compressive strength prediction
Navaratnarajah Sathiparan
Innovative Infrastructure Solutions (2025) Vol. 10, Iss. 3
Closed Access
Ultrasonic detection and deep learning for high-precision concrete strength prediction
Xu Gan, Wei Wang, Chenhui Jiang, et al.
Journal of Building Engineering (2025), pp. 112372-112372
Closed Access
Machine learning models for predicting the compressive strength of agro-waste stabilized bricks for sustainable buildings
Ifeyinwa Ijeoma Obianyo, Jonathan Timothy Auta, David Sciacca, et al.
Deleted Journal (2024) Vol. 1, Iss. 1
Open Access | Times Cited: 4
Prediction of the Dynamic Properties of Concrete Using Artificial Neural Networks
Amjad A. Yasin
Civil Engineering Journal (2024) Vol. 10, Iss. 1, pp. 249-264
Open Access | Times Cited: 3
Recent advances in embedded technologies and self‐sensing concrete for structural health monitoring
Marco Civera, Ahmad Naseem, Bernardino Chiaia
Structural Concrete (2024)
Open Access | Times Cited: 2
Modelling the properties of aerated concrete on the basis of raw materials and ash-and-slag wastes using machine learning paradigm
О. В. Руденко, Darya Galkina, Marzhan Anuarbekovna Sadenova, et al.
Frontiers in Materials (2024) Vol. 11
Open Access | Times Cited: 2
Optimization of Tuff Stones Content in Lightweight Concrete Using Artificial Neural Networks
Amjad A. Yasin, Mohammad T. Awwad, Ahmad B. Malkawi, et al.
Civil Engineering Journal (2023) Vol. 9, Iss. 11, pp. 2823-2833
Open Access | Times Cited: 6
A Review of Effect of Mineral Admixtures on Appearance Quality of Fair-Faced Concrete and Techniques for Their Measurement
Jia-bing Mao, Zhihai He, Yifeng He, et al.
Sustainability (2023) Vol. 15, Iss. 19, pp. 14623-14623
Open Access | Times Cited: 5
A Comparative Analysis of Compressive and Flexural Strength in Concrete with Partial Cement Replacement using Waste Glass Powder
Hedayat Ullah Safi, Mohammad Mukhlis Behsoodi, Mohammad Naseer Sharifi
Indonesian Journal of Material Research (2024) Vol. 2, Iss. 1, pp. 16-22
Open Access | Times Cited: 1
Artificial Neural Network-Based Prediction of Physical and Mechanical Properties of Concrete Containing Glass Aggregates
Faroq Maraqa, Amjad A. Yasin, Eid Al-Sahawneh, et al.
Civil Engineering Journal (2024) Vol. 10, Iss. 5, pp. 1627-1644
Open Access | Times Cited: 1
Estimating the Workability of Concrete with a Stereovision Camera during Mixing
Teemu Ojala, Jouni Punkki
Sensors (2024) Vol. 24, Iss. 14, pp. 4472-4472
Open Access | Times Cited: 1
A Meta-Analysis of the Effect of Moisture Content of Recycled Concrete Aggregate on the Compressive Strength of Concrete
SungWon Cho, Sung-Eun Cho, Alexander S. Brand
Applied Sciences (2024) Vol. 14, Iss. 8, pp. 3512-3512
Open Access
Computer Vision-Driven Multi-Target Recognition and Dynamic Tracking
Zongzhi Lou, Yunxuan Liu, Chengcheng Jiang, et al.
(2024), pp. 196-202
Closed Access
Experimental Investigation of Compressive Strength of Concrete through Conventional Concrete Mixer and Design of Automated Concrete Mixer with Machine Learning
Mr. Kamlesh Dayanand Patle
International Journal for Research in Applied Science and Engineering Technology (2023) Vol. 11, Iss. 10, pp. 1846-1850
Open Access
Machine Learning - Based Prediction of Compressive Strength Analysis
R. Gowri, P. Vasanthi, R. Swathi Rekha, et al.
(2023), pp. 1-4
Closed Access
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