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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:

Predicting the thermal conductivity of soils using integrated approach of ANN and PSO with adaptive and time-varying acceleration coefficients
Navid Kardani, Abidhan Bardhan, Pijush Samui, et al.
International Journal of Thermal Sciences (2021) Vol. 173, pp. 107427-107427
Closed Access | Times Cited: 79

Showing 1-25 of 79 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: 173
Predicting uniaxial compressive strength of rocks using ANN models: Incorporating porosity, compressional wave velocity, and schmidt hammer data
Panagiotis G. Asteris, Μαρία Καρόγλου, Athanasia D. Skentou, et al.
Ultrasonics (2024) Vol. 141, pp. 107347-107347
Closed Access | Times Cited: 48
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: 2
Prediction of the resilient modulus of compacted subgrade soils using ensemble machine learning methods
Navid Kardani, Mohammad Aminpour, Muhammad Nouman Amjad Raja, et al.
Transportation Geotechnics (2022) Vol. 36, pp. 100827-100827
Closed Access | Times Cited: 60
Prediction of the Seismic Effect on Liquefaction Behavior of Fine-Grained Soils Using Artificial Intelligence-Based Hybridized Modeling
Sufyan Ghani, Sunita Kumari, Shamsad Ahmad
Arabian Journal for Science and Engineering (2022) Vol. 47, Iss. 4, pp. 5411-5441
Closed Access | Times Cited: 47
Application of Bio and Nature-Inspired Algorithms in Agricultural Engineering
Chrysanthos Maraveas, Panagiotis G. Asteris, Konstantinos G. Arvanitis, et al.
Archives of Computational Methods in Engineering (2022) Vol. 30, Iss. 3, pp. 1979-2012
Open Access | Times Cited: 42
Multi-expression programming based prediction of the seismic capacity of reinforced concrete rectangular columns
Raheel Asghar, Muhammad Faisal Javed, Muhammad Saqib, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 131, pp. 107834-107834
Closed Access | Times Cited: 11
Development of hybrid models using metaheuristic optimization techniques to predict the carbonation depth of fly ash concrete
Rahul Biswas, Enming Li, Ning Zhang, et al.
Construction and Building Materials (2022) Vol. 346, pp. 128483-128483
Closed Access | Times Cited: 31
Advanced Tree-Based Techniques for Predicting Unconfined Compressive Strength of Rock Material Employing Non-Destructive and Petrographic Tests
Yuzhen Wang, Mahdi Hasanipanah, Ahmad Safuan A. Rashid, et al.
Materials (2023) Vol. 16, Iss. 10, pp. 3731-3731
Open Access | Times Cited: 20
Investigation on the fracture mechanism and constitutive relations of a typical Ni-based superalloy
Xiao–Min Chen, Liao–Yuan Nie, Hongwei Hu, et al.
Materials Today Communications (2023) Vol. 35, pp. 105612-105612
Open Access | Times Cited: 18
Utilizing Construction and Demolition Waste in Concrete as a Sustainable Cement Substitute: A Comprehensive Study on Behavior Under Short-term Dynamic and Static Loads via Laboratory and Numerical Analysis
Mohammad Mohtasham Moein, Komeil Rahmati, Ali Mohtasham Moein, et al.
Journal of Building Engineering (2024), pp. 110778-110778
Closed Access | Times Cited: 5
Application of novel deep neural network on prediction of compressive strength of fly ash based concrete
Rahul Biswas, Manish Kumar, Divesh Ranjan Kumar, et al.
Nondestructive Testing And Evaluation (2024), pp. 1-31
Closed Access | Times Cited: 5
Reliability Analysis of External Stabilities of Reinforced Soil Wall Using Monte Carlo Simulation and an Efficient Hybrid Artificial Neural Network Paradigm
Sudeep Kumar, Avijit Burman
Transportation Infrastructure Geotechnology (2025) Vol. 12, Iss. 1
Closed Access
Effect of Soil Salinity on Thermal Behavior of Sandy Soils Under a Sahara Climate
Djihad Bennaceur, Nadia Laredj, Mustapha Maliki, et al.
Science Engineering and Technology (2025) Vol. 5, Iss. 1
Open Access
Revealing the nature of soil liquefaction using machine learning
Sufyan Ghani, Ishwor Thapa, Amrendra Kumar, et al.
Earth Science Informatics (2025) Vol. 18, Iss. 2
Open Access
BGG-REPT and ROF-REPT: ensemble machine learning models for the prediction of compressive strength of concrete
Binh Thai Pham
Innovative Infrastructure Solutions (2025) Vol. 10, Iss. 2
Closed Access
Optimized neural network for soil moisture prediction in precision agriculture
Prity Soni, Rohit Kumar, Sudhanshu Mishra, et al.
Measurement (2025), pp. 117380-117380
Closed Access
Developing Predictive Models of Collapse Settlement and Coefficient of Stress Release of Sandy-Gravel Soil via Evolutionary Polynomial Regression
Ali Reza Ghanizadeh, Ali Delaram, Pouyan Fakharian, et al.
Applied Sciences (2022) Vol. 12, Iss. 19, pp. 9986-9986
Open Access | Times Cited: 26
How to improve machine learning models for lithofacies identification by practical and novel ensemble strategy and principles
Shaoqun Dong, Yan-Ming Sun, Tao Xu, et al.
Petroleum Science (2022) Vol. 20, Iss. 2, pp. 733-752
Open Access | Times Cited: 24
The application of deep neural networks for the prediction of California Bearing Ratio of road subgrade soil
Kareem Othman, Hassan T. Abdelwahab
Ain Shams Engineering Journal (2022) Vol. 14, Iss. 7, pp. 101988-101988
Open Access | Times Cited: 22
Simulation of soil thermal conductivity based on different schemes: An empirical comparison of 13 models
Wenhao Liu, Ren Li, Tonghua Wu, et al.
International Journal of Thermal Sciences (2023) Vol. 190, pp. 108301-108301
Closed Access | Times Cited: 12
Machine learning-based prediction of shear strength of steel reinforced concrete columns subjected to axial compressive load and seismic lateral load
Siyuan Wang, Jinjun Xu, Yanlin Wang, et al.
Structures (2023) Vol. 56, pp. 104968-104968
Closed Access | Times Cited: 12
Enhancing BOD5 Forecasting Accuracy with the ANN-Enhanced Runge Kutta Model
Rana Muhammad Adnan, Ahmed A. Ewees, Mo Wang, et al.
Journal of environmental chemical engineering (2025), pp. 115430-115430
Closed Access
Fine-tuning of Experimentally Obtained Particle Damper Parameters Using Hybrid Radial Basis Function Neural Network for Vibration Mitigation of a PCB Enclosure
Sunil Kumar, Anil Kumar
Journal of Vibration Engineering & Technologies (2025) Vol. 13, Iss. 2
Closed Access
Investigation on Thermal Conductivity of Soil Under Freeze–Thaw Action Based on Machine Learning Models
Yuwei Chen, Min Yang, Haiqiang Jiang, et al.
Buildings (2025) Vol. 15, Iss. 5, pp. 750-750
Open Access
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