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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:

Ensemble Tree-Based Approach towards Flexural Strength Prediction of FRP Reinforced Concrete Beams
Muhammad Nasir Amin, Mudassir Iqbal, Kaffayatullah Khan, et al.
Polymers (2022) Vol. 14, Iss. 7, pp. 1303-1303
Open Access | Times Cited: 31

Showing 1-25 of 31 citing articles:

Prediction of rapid chloride penetration resistance of metakaolin based high strength concrete using light GBM and XGBoost models by incorporating SHAP analysis
Anas Abdulalim Alabdullah, Mudassir Iqbal, Muhammad Zahid, et al.
Construction and Building Materials (2022) Vol. 345, pp. 128296-128296
Closed Access | Times Cited: 178
Estimating compressive strength of lightweight foamed concrete using neural, genetic and ensemble machine learning approaches
Babatunde Abiodun Salami, Mudassir Iqbal, Abdulazeez Abdulraheem, et al.
Cement and Concrete Composites (2022) Vol. 133, pp. 104721-104721
Open Access | Times Cited: 91
Applications of natural and synthetic fiber reinforced polymer in infrastructure: A suitability assessment
Satheeskumar Navaratnam, Kajanan Selvaranjan, Darshana Jayasooriya, et al.
Journal of Building Engineering (2023) Vol. 66, pp. 105835-105835
Closed Access | Times Cited: 82
Forecasting the strength of graphene nanoparticles-reinforced cementitious composites using ensemble learning algorithms
Majid Khan, Roz‐Ud‐Din Nassar, Waqar Anwar, et al.
Results in Engineering (2024) Vol. 21, pp. 101837-101837
Open Access | Times Cited: 28
Prediction of Stress–Strain Curves for HFRP Composite Confined Brick Aggregate Concrete under Axial Load
Panumas Saingam, Ali Ejaz, Nazam Ali, et al.
Polymers (2023) Vol. 15, Iss. 4, pp. 844-844
Open Access | Times Cited: 27
Structural assessment of Basalt FRP reinforced self-compacting geopolymer concrete using artificial neural network (ANN) modelling
Sherin Khadeeja Rahman, Riyadh Al-Ameri
Construction and Building Materials (2023) Vol. 397, pp. 132464-132464
Open Access | Times Cited: 23
Intelligent prediction modeling for flexural capacity of FRP-strengthened reinforced concrete beams using machine learning algorithms
Majid Khan, Adil Khan, Asad U. Khan, et al.
Heliyon (2023) Vol. 10, Iss. 1, pp. e23375-e23375
Open Access | Times Cited: 22
Boosting-Based Machine Learning Applications in Polymer Science: A Review
Ivan Malashin, В С Тынченко, Andrei Gantimurov, et al.
Polymers (2025) Vol. 17, Iss. 4, pp. 499-499
Open Access | Times Cited: 1
Estimating Flexural Strength of FRP Reinforced Beam Using Artificial Neural Network and Random Forest Prediction Models
Kaffayatullah Khan, Mudassir Iqbal, Babatunde Abiodun Salami, et al.
Polymers (2022) Vol. 14, Iss. 11, pp. 2270-2270
Open Access | Times Cited: 29
Machine Learning Approach for Prediction of Lateral Confinement Coefficient of CFRP-Wrapped RC Columns
Xingsi Xue, Celestine Makota, Osamah Ibrahim Khalaf, et al.
Symmetry (2023) Vol. 15, Iss. 2, pp. 545-545
Open Access | Times Cited: 16
Investigation of transverse reinforcement for R.C flat slabs against punching shear and comparison with innovative strengthening technique using FRP ropes
Mohamed H. Makhlouf, Gamal M. Ismail, Ahmed H. Abdel Kreem, et al.
Case Studies in Construction Materials (2023) Vol. 18, pp. e01935-e01935
Open Access | Times Cited: 13
Enhancing Moment Capacity Prediction in FRP-Reinforced Concrete Beams through Soft Computing Models
Reza Andasht Kazeroon, Nima Ezami, Seyed Mohammad Khatami, et al.
Journal of structural design and construction practice. (2025) Vol. 30, Iss. 2
Closed Access
Development of prediction models for strength properties of concrete using gene expression programming
Asad U. Khan, Muhammad Faisal Javed, Majid Khan
Innovative Infrastructure Solutions (2025) Vol. 10, Iss. 3
Closed Access
Computational AI Models for Investigating the Radiation Shielding Potential of High-Density Concrete
Muhammad Nasir Amin, Izaz Ahmad, Mudassir Iqbal, et al.
Materials (2022) Vol. 15, Iss. 13, pp. 4573-4573
Open Access | Times Cited: 20
Prediction Models for Estimating Compressive Strength of Concrete Made of Manufactured Sand Using Gene Expression Programming Model
Kaffayatullah Khan, Babatunde Abiodun Salami, Arshad Jamal, et al.
Materials (2022) Vol. 15, Iss. 17, pp. 5823-5823
Open Access | Times Cited: 19
Incorporating sea sand into self-compacting concrete: a systematic review
B. M. Sindhurashmi, Gopinatha Nayak, N. D. Adesh, et al.
Deleted Journal (2024) Vol. 6, Iss. 4
Open Access | Times Cited: 4
GEP Tree-Based Prediction Model for Interfacial Bond Strength of Externally Bonded FRP Laminates on Grooves with Concrete Prism
Muhammad Nasir Amin, Mudassir Iqbal, Arshad Jamal, et al.
Polymers (2022) Vol. 14, Iss. 10, pp. 2016-2016
Open Access | Times Cited: 18
Predictive modelling of compression strength of waste GP/FA blended expansive soils using multi-expression programming
Muhammad Usama, Hasnain Gardezi, Fazal E. Jalal, et al.
Construction and Building Materials (2023) Vol. 392, pp. 131956-131956
Open Access | Times Cited: 9
Experimental testing and predictive machine learning to determine the mechanical characteristics of corroded reinforcing steel
Benjamin Matthews, Alessandro Palermo, Tom Logan, et al.
Construction and Building Materials (2024) Vol. 438, pp. 137023-137023
Open Access | Times Cited: 3
Prediction Models for Evaluating Resilient Modulus of Stabilized Aggregate Bases in Wet and Dry Alternating Environments: ANN and GEP Approaches
Kaffayatullah Khan, Fazal E. Jalal, Mohsin Ali Khan, et al.
Materials (2022) Vol. 15, Iss. 13, pp. 4386-4386
Open Access | Times Cited: 15
Flexural behavior of beams strengthened with GFRP bars and high‐performance fiber‐reinforced concrete
Yanli Su, Jiaqi Shang, Pu Zhang, et al.
Structural Concrete (2024) Vol. 25, Iss. 2, pp. 1208-1222
Closed Access | Times Cited: 2
Evaluating the Performance of Ensemble Machine Learning Algorithms Over Traditional Machine Learning Algorithms for Predicting Fire Resistance in FRP Strengthened Concrete Beams
H.R. Kumarawadu, Pasindu Weerasinghe, Jude Shalitha Perera
Electronic Journal of Structural Engineering (2024) Vol. 24, Iss. 3, pp. 47-53
Closed Access | Times Cited: 2
Investigating the Bond Strength of FRP Rebars in Concrete under High Temperature Using Gene-Expression Programming Model
Muhammad Nasir Amin, Mudassir Iqbal, Fadi Althoey, et al.
Polymers (2022) Vol. 14, Iss. 15, pp. 2992-2992
Open Access | Times Cited: 9
PCA-Based Hybrid Intelligence Models for Estimating the Ultimate Bearing Capacity of Axially Loaded Concrete-Filled Steel Tubes
Kaffayatullah Khan, Rahul Biswas, Jitendra Gudainiyan, et al.
Materials (2022) Vol. 15, Iss. 18, pp. 6477-6477
Open Access | Times Cited: 9
Roll-Out Deployment Process Analysis of a Fiber Reinforced Polymer (FRP) Composite Tape-Spring Boom
Sicong Wang, Shuhong Xu, Lei Lu, et al.
Polymers (2023) Vol. 15, Iss. 11, pp. 2455-2455
Open Access | Times Cited: 5
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