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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:

Prediction of compressive strength of high-performance concrete (HPC) using machine learning algorithms
Muhammad Imran, Ali Raza, Muhammad Touqeer
Multiscale and Multidisciplinary Modeling Experiments and Design (2023) Vol. 7, Iss. 3, pp. 1881-1894
Closed Access | Times Cited: 10

Showing 10 citing articles:

Prediction of compressive strength of concrete based on improved artificial bee colony-multilayer perceptron algorithm
Ping Li, Yanru Zhang, Jiming Gu, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 5
A reliable approach for classifying metakaolin content of high-Performance concrete via machine learning algorithm
Chao Zhang, Xiaoyong Zhao, Jian Chen, et al.
International Journal of Pavement Engineering (2025) Vol. 26, Iss. 1
Closed Access
Strength and durability predictions of ternary blended nano-engineered high-performance concrete: Application of hybrid machine learning techniques with bio-inspired optimization
Vikrant S. Vairagade, Boskey V. Bahoria, Haytham F. Isleem, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 148, pp. 110470-110470
Closed Access
Predicting the compressive strength of polymer-infused bricks: A machine learning approach with SHAP interpretability
S. Sathvik, Rakesh Kumar, Archudha Arjunasamy, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Effect of plastic fibers on OPC-based concrete in circular economy
Shehroze Ali, Suliman Khan, Muhammad Imran, et al.
Innovative Infrastructure Solutions (2025) Vol. 10, Iss. 2
Closed Access
Machine learning assisted prediction of the mechanical properties of carbon nanotube‐incorporated concrete
Muhammad Imran, Hassan Amjad, Shayan Ali Khan, et al.
Structural Concrete (2024)
Closed Access | Times Cited: 3
Predictive models for properties of hybrid blended modified sustainable concrete incorporating nano-silica, basalt fibers, and recycled aggregates: Application of advanced artificial intelligence techniques
Boskey V. Bahoria, Prashant B. Pande, Sagar W. Dhengare, et al.
Nano-Structures & Nano-Objects (2024) Vol. 40, pp. 101373-101373
Closed Access | Times Cited: 1
Development of biological techniques to prevent corrosion of reinforcing steel bars
Sajid Rasheed, Rao Arslan Khushnood, Ali Raza, et al.
Heliyon (2024) Vol. 10, Iss. 18, pp. e37966-e37966
Open Access
An AI-driven approach for modeling the compressive strength of sustainable concrete incorporating waste marble as an industrial by-product
Ramin Kazemi, Seyedali Mirjalili
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
Predictive Modeling of the Long-term Effects of Combined Chemical Admixtures on Concrete Compressive Strength Using Machine Learning Algorithms
S. Heidari, Majid Safehian, Faramarz Moodi, et al.
Case Studies in Chemical and Environmental Engineering (2024) Vol. 10, pp. 101008-101008
Open Access
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