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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 California Bearing Ratio Using Soil Index Properties by Regression and Machine-Learning Techniques
Mohammad A. Khasawneh, Haneen I. Al-Akhrass, Samer R. Rabab’ah, et al.
International Journal of Pavement Research and Technology (2022) Vol. 17, Iss. 2, pp. 306-324
Closed Access | Times Cited: 25

Showing 25 citing articles:

A Scientometrics Review of Soil Properties Prediction Using Soft Computing Approaches
Jitendra Khatti, Kamaldeep Singh Grover
Archives of Computational Methods in Engineering (2023) Vol. 31, Iss. 3, pp. 1519-1553
Closed Access | Times Cited: 22
A Comparative Analysis of the Predictive Performance of Tree-Based and Artificial Neural Network Approaches for Compressive Strength of Concrete Utilising Waste
Suhaib Rasool Wani, Manju Suthar
International Journal of Pavement Research and Technology (2024)
Closed Access | Times Cited: 6
Natural Gradient Boosting for Probabilistic Prediction of Soaked CBR Values Using an Explainable Artificial Intelligence Approach
E.F. González Díaz, Giovanni Spagnoli
Buildings (2024) Vol. 14, Iss. 2, pp. 352-352
Open Access | Times Cited: 5
Using soft computing to forecast the strength of concrete utilized with sustainable natural fiber reinforced polymer composites
Suhaib Rasool Wani, Manju Suthar
Asian Journal of Civil Engineering (2024) Vol. 25, Iss. 8, pp. 5847-5863
Closed Access | Times Cited: 5
Prediction of Spatial Soil-California Bearing Ratio of Subgrade Soil Using Particle Swarm Optimization—Artificial Intelligence Method
Yonas Tilahun, Qinghua Xiao, Argaw Asha Ashango, et al.
Transportation Infrastructure Geotechnology (2025) Vol. 12, Iss. 1
Closed Access
Evolutionary Polynomial Regression Model to Predict Effective Angle of Internal Friction of Fine-Grained Soils
Saif Alzabeebee, Bashar Ismael, Suraparb Keawsawasvong, et al.
Transportation Infrastructure Geotechnology (2025) Vol. 12, Iss. 2
Closed Access
Sustainable Soil Reinforcement by Maximizing Geotechnical Performance with Rice Husk Ash in Subgrade Layers
Abdelmageed Atef, Zakaria Hossain
Materials (2025) Vol. 18, Iss. 4, pp. 873-873
Open Access
A Systematic Evaluation of the Empirical Relationships Between the Resilient Modulus and Permanent Deformation of Pavement Materials
Zeping Yang, Junyu Sun, Yupeng Zhang, et al.
Buildings (2025) Vol. 15, Iss. 5, pp. 663-663
Open Access
Applications of machine learning and traditional prediction techniques for estimating resilient modulus values of unbound granular materials incorporating reclaimed asphalt pavement (RAP) as a primary component
Muhammad Arshad, Hafiz Muhammad Hamza
Construction and Building Materials (2025) Vol. 473, pp. 140900-140900
Closed Access
Waste Vegetable Oil as a Sustainable Additive for Enhancing Asphalt Binder Properties: A Review
Mohammad Ali Khasawneh, Ansam Sawalha, Ahmad Al-Khasawneh, et al.
Springer proceedings in physics (2025), pp. 153-164
Closed Access
Evaluating the efficiency of artificial neural networks and tree-based techniques for forecasting the flexural strength of concrete using waste foundry sand
Suhaib Rasool Wani, Manju Suthar
Asian Journal of Civil Engineering (2024) Vol. 25, Iss. 7, pp. 5481-5503
Closed Access | Times Cited: 3
Prediction of California Bearing Ratio of nano-silica and bio-char stabilized soft sub-grade soils using explainable machine learning
Ishwor Thapa, Sufyan Ghani, Kenue Abdul Waris, et al.
Transportation Geotechnics (2024), pp. 101387-101387
Closed Access | Times Cited: 3
Machine learning and RSM-CCD analysis of green concrete made from waste water plastic bottle caps: Towards performance and optimization
Mohammed Nayeemuddin, Andi Asiz, Mohammad Ali Khasawneh, et al.
Mechanics of Advanced Materials and Structures (2023) Vol. 31, Iss. 25, pp. 6829-6837
Closed Access | Times Cited: 7
Influence of mineralogical and geochemical multi-parameters on the geotechnical properties of gneiss-derived lateritic gravels from an equatorial zone, center Cameroon
Aloys Thierry Ndzié Mvindi, Lise Carole Okomo Atouba, Marie Thérèse Nanga Bineli, et al.
Arabian Journal of Geosciences (2024) Vol. 17, Iss. 5
Closed Access | Times Cited: 2
Physical properties of crumb rubber modified asphalt binders and environmental impact consideration
Mohammad Ali Khasawneh, Samar D. Dernayka, Saidur Rahman Chowdhury
Mechanics of Advanced Materials and Structures (2023) Vol. 31, Iss. 26, pp. 7678-7692
Closed Access | Times Cited: 4
Prediction of California bearing ratio using hybrid regression models
Weiwei Wang, Long Zhao, Daoliang Dong
Signal Image and Video Processing (2024) Vol. 18, Iss. 8-9, pp. 6405-6418
Closed Access | Times Cited: 1
Predicting CBR values using gaussian process regression and meta-heuristic algorithms in geotechnical engineering
Xu Wu, Feng Yang, Shuchen Huang
Multiscale and Multidisciplinary Modeling Experiments and Design (2024) Vol. 7, Iss. 4, pp. 3799-3813
Closed Access
Obtaining the California Bearing Ratio Prediction via Hybrid Composition of Random Forest
Bensheng Wu, Yan Zheng
International Journal of Advanced Computer Science and Applications (2024) Vol. 15, Iss. 6
Open Access
Discussion of ‘Strength Evaluation of Expansive Soil Stabilized with Lead–Zinc Mine Tailings and Cement: An Artificial Intelligence Approach’ [DOI: 10.1007/s42947-024–00450-y]
Amin Soltani, Mahdieh Azimi
International Journal of Pavement Research and Technology (2024)
Open Access
Modeling of the effect of gradation and compaction characteristics on the california bearing ratio of granular materials for subbase and landfill liner construction
Majed Alzara, Kennedy C. Onyelowe, Ahmed M. Ebid, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
Integrating Soil Index Parameters and Machine Learning for Reliable California Bearing Ratio Estimation using a GA-ELM Model
Mohammad Ali Khasawneh, Hiren Mewada, Mohammed Nayeemuddin, et al.
International Journal of Pavement Research and Technology (2024)
Closed Access
The State-of-the-Art Review on Prediction of Subgrade CBR: Past and Present Trends
Md Asif Hasan, Ballem Praveen, Ramakrishna Bag, et al.
Indian geotechnical journal (2024)
Closed Access
Implementation of Artificial Neural Network for Forecasting California Bearing Ratio of Treated Cement-Laterite Soil Improved with Bamboo Leaf Ash
Emeka S. Nnochiri, Imhade P. Okokpujie, Rajneesh Kumar Singh
Revue des composites et des matériaux avancés (2024) Vol. 34, Iss. 6, pp. 755-765
Closed Access
Application of hybrid modeling to predict California bearing ratio of soil
Huong Thi Thanh Ngo, Quynh- Anh Thi Bui, Vi Nguyen Van, et al.
VIETNAM JOURNAL OF EARTH SCIENCES (2024)
Open Access
Onsite Estimation of California Bearing Ratio of Subgrade Using Sensor Acceleration
Yogesh Bafna, Jigisha Vashi, Santosh Bothe
Indian geotechnical journal (2024)
Closed Access
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