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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 geopolymer concrete using a hybrid ensemble of grey wolf optimized machine learning estimators
Suraj Kumar Parhi, Sanjaya Kumar Patro
Journal of Building Engineering (2023) Vol. 71, pp. 106521-106521
Closed Access | Times Cited: 74

Showing 26-50 of 74 citing articles:

Rheological behavior of 3D printed concrete: influential factors and printability prediction scheme
Huaxing Gao, Lang Jin, Yuxuan Chen, et al.
Journal of Building Engineering (2024) Vol. 91, pp. 109626-109626
Open Access | Times Cited: 6
Explainable hybridized ensemble machine learning for the prognosis of the compressive strength of recycled plastic-based sustainable concrete with experimental validation
Sanjog Chhetri Sapkota, Ajay Yadav, Ajaya Khatri, et al.
Multiscale and Multidisciplinary Modeling Experiments and Design (2024) Vol. 7, Iss. 6, pp. 6073-6096
Closed Access | Times Cited: 6
Comparative Analysis of Machine Learning Models for Predicting Interfacial Bond Strength of Fiber-Reinforced Polymer-Concrete
Miljan Kovačević, Marijana Hadzima-Nyarko, Predrag Petronijević, et al.
Computation (2025) Vol. 13, Iss. 1, pp. 17-17
Open Access
Predicting the shield effectiveness of carbon fiber reinforced mortars utilizing metaheuristic algorithms
Mana Alyami, Irfan Ullah, Furqan Ahmad, et al.
Case Studies in Construction Materials (2025), pp. e04357-e04357
Open Access
Machine learning-based prediction of optimal GFRP thickness for enhanced circular concrete column confinement
Imane Djafar-Henni, Amina Sadouki
Multiscale and Multidisciplinary Modeling Experiments and Design (2025) Vol. 8, Iss. 3
Closed Access
Frost resistance of steel fiber geopolymer concrete studied via the machine learning method
Xiaoxiao Wang, Haodong Zhang, Liqiang Yin, et al.
Structures (2025) Vol. 73, pp. 108444-108444
Closed Access
Optimizing the utilization of Metakaolin in pre-cured geopolymer concrete using ensemble and symbolic regressions
Kennedy C. Onyelowe, Viroon Kamchoom‬, Ahmed M. Ebid, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Application of metaheuristic spotted hyena optimization in strength prediction of concrete
Suraj Kumar Parhi, Saubhagya Kumar Panigrahi
Elsevier eBooks (2025), pp. 229-248
Closed Access
Prediction of compressive and flexural strength of coal gangue-based geopolymer using machine learning method
Yuxuan Zeng, Yanbing Chen, Yizhou Liu, et al.
Materials Today Communications (2025) Vol. 44, pp. 112076-112076
Closed Access
How Can We Assess Long-Term Multiple Properties Using Only Very Little High-Variance Experimental Data Fused Physical Information?-A Real-Life Concrete Dam Application
Yunguo Cheng, Mengxi Zhang, Dan Tian, et al.
(2025)
Closed Access
Machine Learning and Sustainable Geopolymer Materials: A Systematic Review
Ho Anh Thu Nguyen, Duy Hoang Pham, Yonghan Ahn, et al.
Materials Today Sustainability (2025) Vol. 30, pp. 101095-101095
Open Access
Different machine learning approaches to predict the compressive strength of composite cement concrete
Md. Nafiuzzaman, Tausif Ibn Jakir, Israt Jahan Aditi, et al.
Journal of Building Pathology and Rehabilitation (2025) Vol. 10, Iss. 2
Closed Access
Analyzing the Behavior of Geopolymer Concrete with Different Novel Machine-Learning Algorithms
Sanjog Chhetri Sapkota, Dipak Dahal, Ajay Kumar Yadav, et al.
Journal of structural design and construction practice. (2025) Vol. 30, Iss. 3
Closed Access
Machine learning approach for predicting the compressive strength of ultra-high performance fiber reinforced concrete (UHPFRC)
S. Wijesundara, K. K. Wijesundara, Sahan Bandara
Structures (2025) Vol. 75, pp. 108704-108704
Closed Access
Evaluating the compressive strength of industrial wastes-based geopolymer concrete with machine learning models
Néstor Ulloa, María León, Luis Felipe Silva Palmay, et al.
Construction and Building Materials (2025) Vol. 472, pp. 140891-140891
Closed Access
A new intelligent sunflower optimization based explainable artificial intelligence approach for early‐age concrete compressive strength classification and mixture design of RAC
Muhammed Ulucan, Güngör Yıldırım, Bilal Alataş, et al.
Structural Concrete (2023) Vol. 24, Iss. 6, pp. 7400-7418
Closed Access | Times Cited: 14
Efficient compressive strength prediction of concrete incorporating industrial wastes using deep neural network
Kumar Shubham, Mrutyunjay Rout, Abdhesh Kumar Sinha
Asian Journal of Civil Engineering (2023) Vol. 24, Iss. 8, pp. 3473-3490
Closed Access | Times Cited: 14
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
Performance of precursor characteristics in the realization of geopolymer concrete: a review
Saswat Dwibedy, Suraj Kumar Parhi, Soumyaranjan Panda, et al.
Magazine of Concrete Research (2024) Vol. 76, Iss. 24, pp. 1404-1423
Closed Access | Times Cited: 4
Predicting the compressive strength of engineered geopolymer composites using automated machine learning
Mahmoud Anwar Gad, Ehsan Nikbakht, Mohammed Gamal Ragab
Construction and Building Materials (2024) Vol. 442, pp. 137509-137509
Closed Access | Times Cited: 4
A novel framework for strength prediction of geopolymer mortar: Renovative precursor effect
Zafer Kurt, Yıldıran Yılmaz, Talip Çakmak, et al.
Journal of Building Engineering (2023) Vol. 76, pp. 107041-107041
Closed Access | Times Cited: 11
Mechanics and microstructure analysis of geopolymer utilizing ilmenite tailing and metakaolin powder as alkali-activated materials
Jingqiu Zeng, Kaiqian Zhang, Weiming Sun, et al.
Case Studies in Construction Materials (2024) Vol. 21, pp. e03567-e03567
Open Access | Times Cited: 3
Utilizing ensemble machine learning and gray wolf optimization to predict the compressive strength of silica fume mixtures
Alireza Javid, Vahab Toufigh
Structural Concrete (2024) Vol. 25, Iss. 5, pp. 4048-4074
Closed Access | Times Cited: 2
Prediction of split tensile strength of recycled aggregate concrete leveraging explainable hybrid XGB with optimization algorithm
Sanjog Chhetri Sapkota, Sagar Sapkota, Gaurav Saini
Multiscale and Multidisciplinary Modeling Experiments and Design (2024) Vol. 7, Iss. 4, pp. 4343-4359
Closed Access | Times Cited: 2
Enhanced Support Vector Machine Based on Grey Wolf Optimizer for Fruits Image Classification using MPEG-7 Color and Texture Features Fusion
Joko Siswantoro
International journal of intelligent engineering and systems (2024) Vol. 17, Iss. 3, pp. 1-11
Open Access | Times Cited: 2

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