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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:

Study on predicting compressive strength of concrete using supervised machine learning techniques
B. Vamsi Varma, Elluri Venkata Prasad, Sudhakar Singha
Asian Journal of Civil Engineering (2023) Vol. 24, Iss. 7, pp. 2549-2560
Closed Access | Times Cited: 22

Showing 22 citing articles:

AI-driven Modeling for the Optimization of Concrete Strength for Low-Cost Business Production in the USA Construction Industry
Md. Habibur Rahman Sobuz, Md. Abu Saleh, Md. Samiun, et al.
Engineering Technology & Applied Science Research (2025) Vol. 15, Iss. 1, pp. 20529-20537
Open Access | Times Cited: 2
Explainable XGBoost machine learning model for prediction of ultimate load and free end slip of GFRP rod glued-in timber joints through a pull-out test under various harsh environmental conditions
Nima Tajik, Alireza Mahmoudian, Mostafa Mohammadzadeh Taleshi, et al.
Asian Journal of Civil Engineering (2023) Vol. 25, Iss. 1, pp. 141-157
Closed Access | Times Cited: 19
Evaluating machine learning algorithms for predicting compressive strength of concrete with mineral admixture using long short-term memory (LSTM) Technique
Abhilash Gogineni, Mrutyunjay Rout, Kumar Shubham
Asian Journal of Civil Engineering (2023) Vol. 25, Iss. 2, pp. 1921-1933
Closed Access | Times Cited: 16
Optimized ANN-based approach for estimation of shear strength of soil
Ahsan Rabbani, Pijush Samui, Sunita Kumari
Asian Journal of Civil Engineering (2023) Vol. 24, Iss. 8, pp. 3627-3640
Closed Access | Times Cited: 15
Optimization of an Artificial Neural Network Using Four Novel Metaheuristic Algorithms for the Prediction of Rock Fragmentation in Mine Blasting
Ahsan Rabbani, Divesh Ranjan Kumar, Yewuhalashet Fissha, et al.
Journal of The Institution of Engineers (India) Series D (2024)
Closed Access | Times Cited: 5
Predicting compressive strength of concrete using advanced machine learning techniques: a combined dataset approach
Abinash Mandal
Asian Journal of Civil Engineering (2025)
Open Access
Predicting the compressive strength of rubberized concrete incorporating brick powder based on MLP and RBF neural networks
David Sinkhonde, Destine Mashava, Tajebe Bezabih, et al.
Waste Management Bulletin (2025)
Open Access
Prediction of Sonic Log Values Using a Gradient Boosting Algorithm in the 'AB' Field
Nahari Rasif, Widya Utama, Sherly Ardhya Garini, et al.
BIO Web of Conferences (2025) Vol. 157, pp. 07002-07002
Open Access
Smart sustainable architecture: leveraging machine learning for adaptive digital design and resource optimization
Ma’in Abu-shaikha
Asian Journal of Civil Engineering (2024)
Closed Access | Times Cited: 3
Advanced machine learning techniques for predicting concrete mechanical properties: a comprehensive review of models and methodologies
Fangyuan Li, Md. Sohel Rana, Muhammad Ahmed Qurashi
Multiscale and Multidisciplinary Modeling Experiments and Design (2024) Vol. 8, Iss. 1
Closed Access | Times Cited: 2
Prediction of compressive strength of glass fiber-reinforced self-compacting concrete interpretable by machine learning algorithms
Abhilash Gogineni, Mrutyunjay Rout, Kumar Shubham
Asian Journal of Civil Engineering (2023) Vol. 25, Iss. 2, pp. 2015-2032
Closed Access | Times Cited: 6
Estimating the initial fracture energy of concrete using various machine learning techniques
Ibrahim Albaijan, Arsalan Mahmoodzadeh, Adil Hussein Mohammed, et al.
Engineering Fracture Mechanics (2023) Vol. 295, pp. 109776-109776
Closed Access | Times Cited: 4
Metaheuristic machine learning for optimizing sustainable interior design: enhancing aesthetic and functional rehabilitation in housing projects
Mayyadah Fahmi Hussein, Mazin Arabasy, Mohammad Abukeshek, et al.
Asian Journal of Civil Engineering (2024)
Closed Access | Times Cited: 1
A deep learning and machine learning approach to predict neonatal death in the context of São Paulo
Mohon Raihan, Plabon Kumar Saha, Rajan Das Gupta, et al.
International Journal of Public Health Science (IJPHS) (2023) Vol. 13, Iss. 1, pp. 179-179
Open Access | Times Cited: 2
A novel composite machine learning model for the prediction of compressive strength of blended concrete
Elluri Venkata Prasad, S. Rama Krishna, Sudhakar Singha
Journal of Building Pathology and Rehabilitation (2024) Vol. 10, Iss. 1
Closed Access
Method of designing forest road construction scenario with GIS-based calibration using sustainable forestry model
Shunsuke Kaneko, Hyun Bae Kim, Takuyuki Yoshioka
Results in Engineering (2024) Vol. 24, pp. 103078-103078
Open Access
Enhancing the predictive accuracy of recycled aggregate concrete’s strength using machine learning and statistical approaches: a review
Jawad Tariq, Kui Hu, Syed Tafheem Abbas Gillani, et al.
Asian Journal of Civil Engineering (2024)
Closed Access
Predicting Compressive Strength of Concrete Using Advanced Machine Learning Techniques: A Combined Dataset Approach
Ankita Mandal
Research Square (Research Square) (2024)
Open Access
Experimental Study on Strength of Luminous Concrete with Double Admixture of Fly Ash and Slag Powder
Meng Li, Guangxiu Fang, Haonan Wu, et al.
Lecture notes in civil engineering (2024), pp. 375-387
Closed Access
A Machine Learning-Based User-Friendly Approach for Prediction of Traffic-Induced Vibrations and its Application for Parametric Study
Muhammad Faraz Javaid, Rizwan Azam, Shahab E. Saqib, et al.
Journal of The Institution of Engineers (India) Series A (2023) Vol. 105, Iss. 1, pp. 1-13
Closed Access | Times Cited: 1
Comparative Analysis of Machine Learning Techniques for Concrete Compressive Strength Prediction
Fuad Musleh, Ranyah Taha, Abdel Rahman Musleh
(2023), pp. 146-151
Closed Access | Times Cited: 1
Optimized ANN-based Approach for Estimation of Shear Strength of Soil
Ahsan Rabbani, Pijush Samui, Sunita Kumari
Research Square (Research Square) (2023)
Open Access
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