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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:

Progress in Artificial Intelligence-based Prediction of Concrete Performance
Xiangxin Hu, Bixiong Li, Yelan Mo, et al.
Journal of Advanced Concrete Technology (2021) Vol. 19, Iss. 8, pp. 924-936
Open Access | Times Cited: 32

Showing 1-25 of 32 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: 104
Revolutionizing concrete analysis: An in-depth survey of AI-powered insights with image-centric approaches on comprehensive quality control, advanced crack detection and concrete property exploration
Kaustav Sarkar, Amit Shiuly, Krishna Gopal Dhal
Construction and Building Materials (2023) Vol. 411, pp. 134212-134212
Closed Access | Times Cited: 37
Experimental study on the rheological property of cement paste with fly ash and brick powder
Xu Luo, Jianming Gao, Zhaoheng Guo, et al.
Powder Technology (2023) Vol. 426, pp. 118635-118635
Closed Access | Times Cited: 19
Shear Strength Prediction of Slender Steel Fiber Reinforced Concrete Beams Using a Gradient Boosting Regression Tree Method
Amjed Shatnawi, Hana Mahmood Alkassar, Nadia Moneem Al-Abdaly, et al.
Buildings (2022) Vol. 12, Iss. 5, pp. 550-550
Open Access | Times Cited: 28
Predicting the compressive strength of UHPC with coarse aggregates in the context of machine learning
Yan Yuan, Ming Yang, Xiangwen Shang, et al.
Case Studies in Construction Materials (2023) Vol. 19, pp. e02627-e02627
Open Access | Times Cited: 16
Non-uniform Corrosion Mechanism and residual life forecast of marine engineering concrete reinforcement
Pengrui Zhu, Mengmeng Liu
Journal of Engineering Research (2023) Vol. 11, Iss. 2, pp. 100053-100053
Open Access | Times Cited: 11
Heat transfer characteristics and preheating time prediction of conductive rubber active snow melting bridge deck
Zipeng Ma, Haibin Wei, Dongsheng Wei, et al.
Applied Thermal Engineering (2025), pp. 125604-125604
Closed Access
Efektif Kendiliğinden Yerleşen Hafif Beton Dayanımı Tahmini için Farklı Makine Öğrenmesi Algoritmalarının Karşılıklı Değerlendirilmesi
Hakan Güler, Mustafa Ulaş, Merve Açıkgenç Ulaş
Fırat Üniversitesi Mühendislik Bilimleri Dergisi (2025) Vol. 37, Iss. 1, pp. 251-261
Open Access
Predicting the risk of early cracking in massive monolithic foundation slabs using artificial intelligence algorithms
Tatiana Kondratieva, Vasilina Turina, Антон Чепурненко
Construction Materials and Products (2025) Vol. 8, Iss. 1, pp. 6-6
Closed Access
Artificial intelligence approaches in predicting the mechanical properties of natural fiber-reinforced concrete: A comprehensive review
Mohammed Mohammed, Jawad K. Oleiwi, Aeshah M. Mohammed, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 153, pp. 110933-110933
Closed Access
A state-of-the-art review on monitoring technology and characterization of reinforcement corrosion in concrete
Qiang Li, Jinsong Lan, Luming Shen, et al.
Case Studies in Construction Materials (2025), pp. e04780-e04780
Open Access
A Systematic Review on Intelligent Prediction of Inorganic Building Materials Performance
Mengru Li, Zhongyi Zhang, Xiaodie Zeng, et al.
International Journal of Computational Intelligence Systems (2025) Vol. 18, Iss. 1
Open Access
Shear strength of FRP - reinforced concrete deep beams: Extension of beam and arch action model based on data-driven analysis
Phan Duy Nguyen, Vũ Hiệp Đặng
Structures (2025) Vol. 74, pp. 108553-108553
Closed Access
Artificial Intelligence Models for Predicting Mechanical Properties of Recycled Aggregate Concrete (RAC): Critical Review
Amira Hamdy Ali Ahmed, Jin Wu, Mosaad Ali Hussein Ali
Journal of Advanced Concrete Technology (2022) Vol. 20, Iss. 6, pp. 404-429
Open Access | Times Cited: 14
Characterization and prediction of compressive strength in ultralow-temperature frozen soil using nuclear magnetic resonance and WOA-ENN Model
Zhifeng Ren, Enliang Wang, Jiankun Liu, et al.
Transportation Geotechnics (2023) Vol. 43, pp. 101143-101143
Closed Access | Times Cited: 8
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
Research on Hyperparameter Optimization of Concrete Slump Prediction Model Based on Response Surface Method
Yuan Chen, Jiaye Wu, Yingqian Zhang, et al.
Materials (2022) Vol. 15, Iss. 13, pp. 4721-4721
Open Access | Times Cited: 9
Deep learning approaches for prediction of adiabatic temperature rise of concrete with complex mixture constituents
Yu Jiang, Wenqiang Zuo, Chi Yuan, et al.
Journal of Building Engineering (2023) Vol. 73, pp. 106816-106816
Closed Access | Times Cited: 5
Prediction of time-dependent concrete mechanical properties based on advanced deep learning models considering complex variables
Yu Jiang, Jinhao Zhang, Wenqiang Zuo, et al.
Case Studies in Construction Materials (2024) Vol. 21, pp. e03629-e03629
Open Access | Times Cited: 1
Comparative Analysis of Automated Machine Learning and Optimized Conventional Machine Learning for Concrete’s Uniaxial Compressive Strength Prediction
Chukwuemeka Daniel
Advances in Civil Engineering (2024) Vol. 2024, Iss. 1
Open Access | Times Cited: 1
Prediction for snow melting process of conductive ethylene propylene diene monomer composites based on machine learning approaches
Shuanye Han, Haibin Wei, Hongwei Wang, et al.
Construction and Building Materials (2022) Vol. 356, pp. 129315-129315
Closed Access | Times Cited: 6
Application of deep learning in civil engineering: boosting algorithms for predicting strength of concrete
Canrong Xie, Jianjun Wang, Zhiwen Wu, et al.
Journal of Intelligent & Fuzzy Systems (2023) Vol. 45, Iss. 5, pp. 9109-9122
Closed Access | Times Cited: 2
Applications of artificial intelligence in benign prostatic hyperplasia
Saakshi Bansal, Yanjinlkham Chuluunbaatar, Andrew Brodie, et al.
Artificial Intelligence Surgery (2023) Vol. 3, Iss. 2, pp. 129-139
Open Access | Times Cited: 1
Integration of new technologies with sustainable concrete materials and structures
Payam Hosseini
Elsevier eBooks (2024), pp. 641-667
Closed Access
Prediction of Time-Dependent Concrete Mechanical Properties Based on Advanced Deep Learning Models Considering Complex Variables
Yu Jiang, Jinhao Zhang, Wenqiang Zuo, et al.
(2024)
Closed Access
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