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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:

Efficient machine learning algorithm with enhanced cat swarm optimization for prediction of compressive strength of GGBS-based geopolymer concrete at elevated temperature
Pankaj Kumar Dash, Suraj Kumar Parhi, Sanjaya Kumar Patro, et al.
Construction and Building Materials (2023) Vol. 400, pp. 132814-132814
Closed Access | Times Cited: 29

Showing 1-25 of 29 citing articles:

Machine learning approaches to predict compressive strength of fly ash-based geopolymer concrete: A comprehensive review
Madushan Rathnayaka, Dulakshi Karunasinghe, Chamila Gunasekara, et al.
Construction and Building Materials (2024) Vol. 419, pp. 135519-135519
Open Access | Times Cited: 37
Investigation of machine learning models in predicting compressive strength for ultra-high-performance geopolymer concrete: A comparative study
Mohamed Abdellatief, Youssef M. Hassan, Mohamed T. Elnabwy, et al.
Construction and Building Materials (2024) Vol. 436, pp. 136884-136884
Closed Access | Times Cited: 28
AI-driven critical parameter optimization of sustainable self-compacting geopolymer concrete
Suraj Kumar Parhi, Saswat Dwibedy, Saubhagya Kumar Panigrahi
Journal of Building Engineering (2024) Vol. 86, pp. 108923-108923
Closed Access | Times Cited: 23
Metaheuristic optimization of machine learning models for strength prediction of high-performance self-compacting alkali-activated slag concrete
Suraj Kumar Parhi, Soumyaranjan Panda, Saswat Dwibedy, et al.
Multiscale and Multidisciplinary Modeling Experiments and Design (2024) Vol. 7, Iss. 3, pp. 2901-2928
Closed Access | Times Cited: 16
Transfer learning framework for modelling the compressive strength of ultra-high performance geopolymer concrete
Ho Anh Thu Nguyen, Duy Hoang Pham, Anh Tuấn Lê, et al.
Construction and Building Materials (2025) Vol. 459, pp. 139746-139746
Closed Access | Times Cited: 1
Influence of chemical constituents of binder and activator in predicting compressive strength of fly ash-based geopolymer concrete using firefly-optimized hybrid ensemble machine learning model
Pankaj Kumar Dash, Suraj Kumar Parhi, Sanjaya Kumar Patro, et al.
Materials Today Communications (2023) Vol. 37, pp. 107485-107485
Closed Access | Times Cited: 26
Explainable machine learning: Compressive strength prediction of FRP-confined concrete column
Tianyu Hu, Hong Zhang, Cheng Cheng, et al.
Materials Today Communications (2024) Vol. 39, pp. 108883-108883
Closed Access | Times Cited: 8
Mechanical and durability properties of polymer fiber reinforced one-part foam geopolymer concrete: A sustainable strategy for the recycling of waste steel slag aggregate and fly ash
Adem Ahıskalı, Mehtiali Ahıskalı, Oğuzhan Yavuz Bayraktar, et al.
Construction and Building Materials (2024) Vol. 440, pp. 137492-137492
Closed Access | Times Cited: 8
Application of R-curve, ANCOVA, and RSM techniques on fracture toughness enhancement in PET fiber-reinforced concrete
Suraj Kumar Parhi, Sanjaya Kumar Patro
Construction and Building Materials (2023) Vol. 411, pp. 134644-134644
Closed Access | Times Cited: 18
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
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
Deep learning enhanced framework for multi-objective optimization of cement-slag concrete for the balancing performance, economics, and sustainability
Amol Mali, Atul Kolhe, Pravin Gorde, et al.
Asian Journal of Civil Engineering (2025)
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
Towards improved flexural behavior of plastic-based mortars: An experimental and modeling study on waste material incorporation
Yingjie Li, Genhui Wang, Muhammad Nasir Amin, et al.
Materials Today Communications (2024) Vol. 40, pp. 109391-109391
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
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
Multi-objective optimization and prediction of strength along with durability in acid-resistant self-compacting alkali-activated concrete
Suraj Kumar Parhi, Ashutosh Nanda, Saubhagya Kumar Panigrahi
Construction and Building Materials (2024) Vol. 456, pp. 139235-139235
Closed Access | Times Cited: 2
Temperature-Dependent Compressive Strength Modeling of Geopolymer Blocks Utilizing Glass Powder and Steel Slag
Supriya Janga, Ashwin Raut, Alireza Bahrami, et al.
Results in Materials (2024) Vol. 24, pp. 100636-100636
Open Access | Times Cited: 2
Parametric Analysis and Prediction of Geopolymerization Process
Suraj Kumar Parhi, Sanjaya Kumar Patro
Materials Today Communications (2024), pp. 111047-111047
Closed Access | Times Cited: 2
Prediction of the Unconfined Compressive Strength of a One-Part Geopolymer-Stabilized Soil Using Deep Learning Methods with Combined Real and Synthetic Data
Qinyi Chen, Guo Hu, Jun Wu
Buildings (2024) Vol. 14, Iss. 9, pp. 2894-2894
Open Access
Fundamental machine learning algorithms and statistical models applied in strength prediction of geopolymers: a systematic review
Jabulani Matsimbe, Megersa Olumana Dinka, David O. Olukanni, et al.
Deleted Journal (2024) Vol. 6, Iss. 10
Open Access
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