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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 Properties of FRP-Confined Concrete Cylinders Based on Artificial Neural Networks
Afaq Ahmad, Vagelis Plevris, Q.U.Z. Khan
Crystals (2020) Vol. 10, Iss. 9, pp. 811-811
Open Access | Times Cited: 41

Showing 1-25 of 41 citing articles:

Predictive models for concrete properties using machine learning and deep learning approaches: A review
Mohammad Mohtasham Moein, Ashkan Saradar, Komeil Rahmati, et al.
Journal of Building Engineering (2022) Vol. 63, pp. 105444-105444
Open Access | Times Cited: 225
Use of Artificial Intelligence for Predicting Parameters of Sustainable Concrete and Raw Ingredient Effects and Interactions
Muhammad Nasir Amin, Waqas Ahmad, Kaffayatullah Khan, et al.
Materials (2022) Vol. 15, Iss. 15, pp. 5207-5207
Open Access | Times Cited: 37
Modeling green recycled aggregate concrete using machine learning and variance-based sensitivity analysis
Mahmoud Owais, Lamiaa K. Idriss
Construction and Building Materials (2024) Vol. 440, pp. 137393-137393
Closed Access | Times Cited: 10
Coupled extreme gradient boosting algorithm with artificial intelligence models for predicting compressive strength of fiber reinforced polymer- confined concrete
Tao Hai, Zainab Hasan Ali, Faisal M. Mukhtar, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 134, pp. 108674-108674
Closed Access | Times Cited: 8
Development of ensemble machine learning approaches for designing fiber-reinforced polymer composite strain prediction model
Abdalrhman Milad, Sadaam Hadee Hussein, Ahlam R. Khekan, et al.
Engineering With Computers (2021) Vol. 38, Iss. 4, pp. 3625-3637
Closed Access | Times Cited: 51
An alternative approach for measuring the mechanical properties of hybrid concrete through image processing and machine learning
Muhammad Imran Waris, Vagelis Plevris, Junaid Mir, et al.
Construction and Building Materials (2022) Vol. 328, pp. 126899-126899
Closed Access | Times Cited: 33
Neural network model for bond strength of FRP bars in concrete
Nolan C. Concha
Structures (2022) Vol. 41, pp. 306-317
Closed Access | Times Cited: 29
Development of a Reliable Machine Learning Model to Predict Compressive Strength of FRP-Confined Concrete Cylinders
Prashant Kumar, Harish Chandra Arora, Alireza Bahrami, et al.
Buildings (2023) Vol. 13, Iss. 4, pp. 931-931
Open Access | Times Cited: 17
Prediction of compressive strength of FRP-confined concrete using machine learning: A novel synthetic data driven framework
Sixiong Zeng, Xin Wang, Luqing Hua, et al.
Journal of Building Engineering (2024) Vol. 94, pp. 109918-109918
Closed Access | Times Cited: 6
Predicting the performance of pervious concrete pavements using artificial intelligence
Abdulkader El-Mir, Dana Nasr, Hilal El-Hassan
Elsevier eBooks (2025), pp. 319-343
Closed Access
Data-driven machine-learning models for predicting non-uniform confinement effects of FRP-confined concrete
Jian Xie, Chenhang Jia, Zhe Wang
Structures (2025) Vol. 74, pp. 108555-108555
Closed Access
Hybrid regression and machine learning model for predicting ultimate condition of FRP-confined concrete
Behrooz Keshtegar, Aliakbar Gholampour, Duc‐Kien Thai, et al.
Composite Structures (2021) Vol. 262, pp. 113644-113644
Closed Access | Times Cited: 38
Estimating the compressive strength of rectangular fiber reinforced polymer–confined columns using multilayer perceptron, radial basis function, and support vector regression methods
Yaser Moodi, Mohammad Ghasemi, Seyed Roohollah Mousavi
Journal of Reinforced Plastics and Composites (2021) Vol. 41, Iss. 3-4, pp. 130-146
Closed Access | Times Cited: 29
Rapid Analysis of CFRP-Reinforced Concrete Structures Using Artificial Neural Networks
Nasim Shakouri Mahmoudabadi, Charles V. Camp
Advances in mechatronics and mechanical engineering (AMME) book series (2024), pp. 60-96
Closed Access | Times Cited: 3
Computational intelligence methods in simulation and modeling of structures: A state-of-the-art review using bibliometric maps
German Solorzano, Vagelis Plevris
Frontiers in Built Environment (2022) Vol. 8
Open Access | Times Cited: 17
Prediction of compressive strength of fiber-reinforced polymers-confined cylindrical concrete using artificial intelligence methods
Faride Jamali, Seyed Roohollah Mousavi, Abdolhamid Bahr Peyma, et al.
Journal of Reinforced Plastics and Composites (2022) Vol. 41, Iss. 17-18, pp. 679-704
Closed Access | Times Cited: 15
Assessment of a technique for faster time integration in application to seismic wave propagation analysis
Ali Lashgari, Aram Soroushian, Hamid Zafarani
Wave Motion (2024) Vol. 130, pp. 103320-103320
Closed Access | Times Cited: 2
Prediction of load-bearing capacity of RC Columns (CWA) using Artificial Neural Networks (ANN) trained on a Hybrid Experimental Database HEXP
Ammar T. Al-Sayegh, Nasim Shakouri Mahmoudabadi, Faisal Shabbir, et al.
Journal of Engineering Research (2024)
Open Access | Times Cited: 2
Application of Group Method of Data Handling on the Ultimate Conditions’ Prediction of FRP-Confined Concrete Cylinders
Chubing Deng, Ruiliang Zhang, Xinhua Xue
Polymers (2022) Vol. 14, Iss. 17, pp. 3615-3615
Open Access | Times Cited: 10
Simulation of Quantity and Quality of Saq Aquifer Using Artificial Intelligence and Hydraulic Models
Abdul Razzaq Ghumman, Ghufran Ahmed Pasha, Md. Shafiquzzaman, et al.
Advances in Civil Engineering (2022) Vol. 2022, Iss. 1
Open Access | Times Cited: 9
Ultimate Conditions Prediction and Stress–Strain Model for FRP-Confined Concrete Using Machine Learning
Jianxin Zhang, Tingwei Zhang, Yueyang Zhai, et al.
Arabian Journal for Science and Engineering (2024) Vol. 49, Iss. 10, pp. 14403-14428
Closed Access | Times Cited: 1
Neural Network-Based Prediction: The Case of Reinforced Concrete Members under Simple and Complex Loading
Afaq Ahmad, Nikos D. Lagaros, Demetrios M. Cotsovos
Applied Sciences (2021) Vol. 11, Iss. 11, pp. 4975-4975
Open Access | Times Cited: 12
Prediction of columns with GFRP bars through Artificial Neural Network and ABAQUS
Afaq Ahmad, Aiman Aljuhni, Muhammad Usman Arshid, et al.
Structures (2022) Vol. 40, pp. 247-255
Closed Access | Times Cited: 7
Predicting the Fundamental Period of Light-Frame Wooden Buildings by Employing Bat Algorithm-Based Artificial Neural Network
Mehdi Nikoo, Ghazanfarah Hafeez, Ghasan Doudak, et al.
Advances in civil and industrial engineering book series (2023), pp. 139-162
Closed Access | Times Cited: 3
An Open-Source Framework for Modeling RC Shear Walls Using Deep Neural Networks
German Solorzano, Vagelis Plevris
Advances in Civil Engineering (2023) Vol. 2023, pp. 1-17
Open Access | Times Cited: 3
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