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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:

Strength prediction and optimization for ultrahigh-performance concrete with low-carbon cementitious materials – XG boost model and experimental validation
M. Iqbal Khan, Yassir M. Abbas, Galal Fares, et al.
Construction and Building Materials (2023) Vol. 387, pp. 131606-131606
Closed Access | Times Cited: 24

Showing 24 citing articles:

Prediction of concrete and FRC properties at high temperature using machine and deep learning: A review of recent advances and future perspectives
Nizar Faisal Alkayem, Lei Shen, Ali Mayya, et al.
Journal of Building Engineering (2023) Vol. 83, pp. 108369-108369
Closed Access | Times Cited: 90
Prediction and optimization model of sustainable concrete properties using machine learning, deep learning and swarm intelligence: A review
Shiqi Wang, Peng Xia, Keyu Chen, et al.
Journal of Building Engineering (2023) Vol. 80, pp. 108065-108065
Closed Access | Times Cited: 57
Hybrid data-driven approaches to predicting the compressive strength of ultra-high-performance concrete using SHAP and PDP analyses
Abul Kashem, Rezaul Karim, Somir Chandra Malo, et al.
Case Studies in Construction Materials (2024) Vol. 20, pp. e02991-e02991
Open Access | Times Cited: 45
Intelligent data-driven compressive strength prediction and optimization of reactive powder concrete using multiple ensemble-based machine learning approach
M. Iqbal Khan, Yassir M. Abbas
Construction and Building Materials (2023) Vol. 404, pp. 133148-133148
Closed Access | Times Cited: 22
Predictive models in machine learning for strength and life cycle assessment of concrete structures
A. Dinesh, B. Rahul Prasad
Automation in Construction (2024) Vol. 162, pp. 105412-105412
Closed Access | Times Cited: 12
Optimizing compressive strength of quaternary-blended cement concrete through ensemble-instance-based machine learning
Ammar Babiker, Yassir M. Abbas, M. Iqbal Khan, et al.
Materials Today Communications (2024) Vol. 39, pp. 109150-109150
Closed Access | Times Cited: 5
Research on the preparation of eco-economical ultra-high performance concrete utilizing graphite tailings resources
Hongbo Liu, Qi Bai, Hangyu Ma, et al.
Construction and Building Materials (2024) Vol. 438, pp. 137102-137102
Closed Access | Times Cited: 5
Utilizing machine learning approaches within concrete technology offers an intelligent perspective towards sustainability in the construction industry: a comprehensive review
Suhaib Rasool Wani, Manju Suthar
Multiscale and Multidisciplinary Modeling Experiments and Design (2024) Vol. 8, Iss. 1
Closed Access | Times Cited: 5
Intelligent prediction and understanding of self-shrinkage in ultra-high performance concrete based on machine learning
Hao Ji, Wenbin Jiao, Xie Xu, et al.
Case Studies in Construction Materials (2025) Vol. 22, pp. e04255-e04255
Open Access
Design of sustainable mortar incorporating construction and demolition waste through adaptive experiments accelerated by machine learning
Thomas Tawiah Baah, Hang Zeng, Marat I. Latypov, et al.
Results in Engineering (2025), pp. 104264-104264
Open Access
Study on the application of discrepancy-guided symbolic regression algorithm in analyzing the impact resistance of UHP-SFRC target against high velocity projectile impact
Delei Zou, Dilyar Thoti, Zhenmin Bao
International Journal of Impact Engineering (2025), pp. 105276-105276
Closed Access
Explainable artificial intelligence-based compressive strength optimization and Life-Cycle Assessment of eco-friendly sugarcane bagasse ash concrete
Varisha Rizwan, Syed Muhammad Ibrahim, Mohd Moonis Zaheer, et al.
Environmental Science and Pollution Research (2025)
Closed Access
Data driven design of ultra high performance concrete prospects and application
Bryan K. Aylas-Paredes, Taihao Han, Advaith Neithalath, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
A systematic literature review of AI-based prediction methods for self-compacting, geopolymer, and other eco-friendly concrete types: Advancing sustainable concrete
Tariq Ali, Mohamed Hechmi El Ouni, Muhammad Zeeshan Qureshi, et al.
Construction and Building Materials (2024) Vol. 440, pp. 137370-137370
Closed Access | Times Cited: 4
Research on prediction of rheological properties of steel-polypropylene fiber UHPC mortar based on ensemble machine learning
X.F. Zhou, Duan Feng, W. Liu, et al.
Construction and Building Materials (2025) Vol. 472, pp. 140833-140833
Closed Access
Optimization of mix proportion and strength prediction of magnesium phosphate cement-based composites based on machine learning
Jing Zhang, Tao Li, Yuanyuan Yao, et al.
Construction and Building Materials (2023) Vol. 411, pp. 134738-134738
Closed Access | Times Cited: 11
Experimental study on tensile and fracture properties of continuous directional steel fibre reactive powder concrete
Wenhao Li, Wuji Lan, Fangyuan Li
Construction and Building Materials (2024) Vol. 433, pp. 136788-136788
Closed Access | Times Cited: 2
Optimized Machine Learning Algorithms for Predicting the Punching Shear Resistance of Flat Slabs with Transverse Reinforcement
Huajun Yan, Nan Xie
International Journal of Concrete Structures and Materials (2024) Vol. 18, Iss. 1
Open Access | Times Cited: 2
Interpretable Machine-Learning Models to Predict the Flexural Strength of Fiber-Reinforced SCM-Blended Concrete Composites
Saad Shamim Ansari, Syed Muhammad Ibrahim, Syed Danish Hasan
Journal of structural design and construction practice. (2024) Vol. 30, Iss. 2
Closed Access | Times Cited: 1
Intelligent condition prediction model for bridge infrastructure based on evaluating machine learning algorithms
Saleh Abu Dabous, Ahmad Alzghoul, Fakhariya Ibrahim
Smart and Sustainable Built Environment (2024)
Closed Access | Times Cited: 1
Effect of Construction Delays and the Preventive Role of Concrete Works Optimization: Systematic Literature Review
Angga Trisna Yudhistira, Iman Satyarno, Arief Setiawan Budi Nugroho, et al.
TEM Journal (2024), pp. 1203-1217
Open Access
Improving Shear Strength Prediction in Steel Fiber Reinforced Concrete Beams: Stacked Ensemble Machine Learning Modeling and Practical Applications
Abdulrahman Albidah, Yassir M. Abbas
Buildings (2024) Vol. 14, Iss. 7, pp. 2169-2169
Open Access
Insightful database-driven prediction and sensitivity analysis of electrical resistivity of nano-graphite-modified cementitious composites: a supervised machine learning regression
Abdulaziz Alsaif, Yassir M. Abbas
Materials Today Communications (2024), pp. 110511-110511
Closed Access
Review of Recent Advances on AI Applications in Civil Engineering
Yaren Aydın, Gebrai̇l Bekdaş, Sinan Melih Niğdeli
Springer tracts in nature-inspired computing (2024), pp. 107-130
Closed Access
Anomaly detection in bridge structural health monitoring via 1D-LBP and statistical feature fusion
Qiankun Zhu, Wenqi Li, Xianyu Wang, et al.
Structures (2024) Vol. 70, pp. 107734-107734
Closed Access
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