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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:

Mixed artificial intelligence models for compressive strength prediction and analysis of fly ash concrete
Wei Liang, Wei Yin, Yu Zhong, et al.
Advances in Engineering Software (2023) Vol. 185, pp. 103532-103532
Closed Access | Times Cited: 21

Showing 21 citing articles:

Machine learning and interactive GUI for concrete compressive strength prediction
Mohamed Kamel Elshaarawy, Mostafa M. Alsaadawi, Abdelrahman Kamal Hamed
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 33
Modelling the compressive strength of geopolymer recycled aggregate concrete using ensemble machine learning
Emadaldin Mohammadi Golafshani, Nima Khodadadi, Tuan Ngo, et al.
Advances in Engineering Software (2024) Vol. 191, pp. 103611-103611
Open Access | Times Cited: 21
Stacked-based machine learning to predict the uniaxial compressive strength of concrete materials
Abdelrahman Kamal Hamed, Mohamed Kamel Elshaarawy, Mostafa M. Alsaadawi
Computers & Structures (2025) Vol. 308, pp. 107644-107644
Closed Access | Times Cited: 5
Exploring LightGBM-SHAP: Interpretable predictive modeling for concrete strength under high temperature conditions
Shaoqiang Meng, Zhenming Shi, Chengzhi Xia, et al.
Structures (2025) Vol. 71, pp. 108134-108134
Closed Access | Times Cited: 2
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: 14
AI-driven design for the compressive strength of ultra-high performance geopolymer concrete (UHPGC): From explainable ensemble models to the graphical user interface
Metin Katlav, Faruk Ergen, İzzeddin Dönmez
Materials Today Communications (2024) Vol. 40, pp. 109915-109915
Closed Access | Times Cited: 10
Data-driven compressive strength prediction of basalt fiber reinforced rubberized concrete using neural network-based models
Chunhua Lü, Chenxi Zhou, Siqi Yuan, et al.
Materials Today Communications (2025), pp. 111706-111706
Closed Access
Machine learning-based prediction of elliptical double steel columns under compression loading
Rende Mu, Haytham F. Isleem, Walaa J. K. Almoghaye, et al.
Journal Of Big Data (2025) Vol. 12, Iss. 1
Open Access
How machine learning can transform the future of concrete
Kaoutar Mouzoun, Azzeddine Bouyahyaoui, Hanane Moulay Abdelali, et al.
Asian Journal of Civil Engineering (2025)
Closed Access
Mechanical properties and microstructural discrepancies of concrete with flotation-modified fly ash from circulating fluidized bed and pulverized coal furnaces
Ruiyan Yu, Jinming Jiang, Shaochun Li, et al.
Construction and Building Materials (2024) Vol. 428, pp. 136320-136320
Closed Access | Times Cited: 2
Influence of Accelerated Carbonation on the Performance of Recycled Concrete Containing Fly Ash, Recycled Coarse Aggregate, and Fine Aggregate
Ziqi Yao, Ling Luo, Yongjun Qin, et al.
Materials (2024) Vol. 17, Iss. 21, pp. 5191-5191
Open Access | Times Cited: 1
Modelling and evaluation of mechanical performance and environmental impacts of sustainable concretes using a multi-objective optimization based innovative interpretable artificial intelligence method
Muhammed Ulucan, Güngör Yıldırım, Bilal Alataş, et al.
Journal of Environmental Management (2024) Vol. 372, pp. 123364-123364
Closed Access | Times Cited: 1
Use of soft computing approaches for the prediction of compressive strength in concrete blends with eggshell powder
Navaratnarajah Sathiparan, Pratheeba Jeyananthan
Journal of Building Pathology and Rehabilitation (2023) Vol. 9, Iss. 1
Closed Access | Times Cited: 2

Khoon Ng Chee
Journal of Civil Engineering Science and Technology (2024) Vol. 15, Iss. 1
Open Access
Experimental Study and Neural Network Prediction on Physical and Mechanical Properties of Coal Gangue-Based Heat Storage Backfill (G-Hsb)
Pai Ning, Feng Ju, Alfonso Rodríguez-Dono, et al.
(2024)
Closed Access
Compressive Strength Prediction of Fly Ash-Based Concrete Using Single and Hybrid Machine Learning Models
Haiyu Li, Heung‐Jin Chung, Zhenting Li, et al.
Buildings (2024) Vol. 14, Iss. 10, pp. 3299-3299
Open Access
Assessing the Strength Characteristics and Environmental Impact of Fly-Ash Geopolymer Mortar for Sustainable Green Patch Repair: A Pathway towards SDGs Achievement
Pinta Astuti, Devi Sasmita, Muhammad Isnaini, et al.
E3S Web of Conferences (2024) Vol. 594, pp. 06001-06001
Open Access
Experimental investigation on compressive strength and environmental performance of paving blocks using fly ash as a substitute for cement and sand
Rikhwanul Dwisetya Ramdi, Muhammad Akbar Caronge, M W Tjaronge
Journal of Building Pathology and Rehabilitation (2024) Vol. 10, Iss. 1
Closed Access
Corrosion Performance of Steel Bar Embedded in Seawater Mixed Mortar with Batching Plant Waste
Pinta Astuti
Diffusion and defect data, solid state data. Part B, Solid state phenomena/Solid state phenomena (2024) Vol. 368, pp. 79-91
Closed Access
Construction and optimization of spatial network structure of waterborne polyurethane modified concrete
Guoxi Fan, Weiqiang Fu, Fei Sha, et al.
Construction and Building Materials (2024) Vol. 458, pp. 139611-139611
Closed Access
The Effect of Anti-corrosion Agent on the Polarization of Rebar in Mortar Mixed by Seawater
Pinta Astuti
(2023), pp. 283-288
Closed Access
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