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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:

Efficient computational techniques for predicting the California bearing ratio of soil in soaked conditions
Abidhan Bardhan, Candan Gökçeoğlu, Avijit Burman, et al.
Engineering Geology (2021) Vol. 291, pp. 106239-106239
Closed Access | Times Cited: 85

Showing 1-25 of 85 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 resilient modulus of flexible pavement foundation using extreme gradient boosting based optimised models
Reza Sarkhani Benemaran, Mahzad Esmaeili‐Falak, Akbar A. Javadi
International Journal of Pavement Engineering (2022) Vol. 24, Iss. 2
Open Access | Times Cited: 82
Prediction of compaction parameters for fine-grained soil: Critical comparison of the deep learning and standalone models
Jitendra Khatti, Kamaldeep Singh Grover
Journal of Rock Mechanics and Geotechnical Engineering (2023) Vol. 15, Iss. 11, pp. 3010-3038
Open Access | Times Cited: 64
Compressive strength of concrete material using machine learning techniques
Satish Paudel, Anil Pudasaini, Rajesh Kumar Shrestha, et al.
Cleaner Engineering and Technology (2023) Vol. 15, pp. 100661-100661
Open Access | Times Cited: 51
Efficient prediction of California bearing ratio in solid waste-cement-stabilized soil using improved hybrid extreme gradient boosting model
Yiliang Tu, Qianglong Yao, Shuitao Gu, et al.
Materials Today Communications (2025) Vol. 43, pp. 111627-111627
Closed Access | Times Cited: 1
Soft computing techniques for the prediction of concrete compressive strength using Non-Destructive tests
Panagiotis G. Asteris, Athanasia D. Skentou, Abidhan Bardhan, et al.
Construction and Building Materials (2021) Vol. 303, pp. 124450-124450
Closed Access | Times Cited: 82
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
Machine learning-based intelligent modeling of hydraulic conductivity of sandy soils considering a wide range of grain sizes
Zia ur Rehman, Usama Khalid, Nauman Ijaz, et al.
Engineering Geology (2022) Vol. 311, pp. 106899-106899
Closed Access | Times Cited: 66
Prediction of flyrock induced by mine blasting using a novel kernel-based extreme learning machine
Mehdi Jamei, Mahdi Hasanipanah, Masoud Karbasi, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2021) Vol. 13, Iss. 6, pp. 1438-1451
Open Access | Times Cited: 56
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
Novel integration of extreme learning machine and improved Harris hawks optimization with particle swarm optimization-based mutation for predicting soil consolidation parameter
Abidhan Bardhan, Navid Kardani, Abdel Kareem Alzo’ubi, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2022) Vol. 14, Iss. 5, pp. 1588-1608
Open Access | Times Cited: 46
Machine learning approach for predicting and evaluating California bearing ratio of stabilized soil containing industrial waste
Lanh Si Ho, Van Quan Tran
Journal of Cleaner Production (2022) Vol. 370, pp. 133587-133587
Closed Access | Times Cited: 37
CBR Prediction of Pavement Materials in Unsoaked Condition Using LSSVM, LSTM-RNN, and ANN Approaches
Jitendra Khatti, Kamaldeep Singh Grover
International Journal of Pavement Research and Technology (2023) Vol. 17, Iss. 3, pp. 750-786
Closed Access | Times Cited: 35
A novel integrated approach of RUNge Kutta optimizer and ANN for estimating compressive strength of self-compacting concrete
Rahul Biswas, Manish Kumar, Raushan Kumar Singh, et al.
Case Studies in Construction Materials (2023) Vol. 18, pp. e02163-e02163
Open Access | Times Cited: 22
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
Use of Machine Learning to Predict California Bearing Ratio of Soils
Semachew Molla Kassa, Betelhem Zewdu Wubineh
Advances in Civil Engineering (2023) Vol. 2023, pp. 1-11
Open Access | Times Cited: 21
A super-learner machine learning model for a global prediction of compression index in clays
E.F. González Díaz, Giovanni Spagnoli
Applied Clay Science (2024) Vol. 249, pp. 107239-107239
Open Access | Times Cited: 10
A comprehensive review of potential protection methods for VSC multi-terminal HVDC systems
Jalal Sahebkar Farkhani, Özgür Çelık, Kaiqi Ma, et al.
Renewable and Sustainable Energy Reviews (2024) Vol. 192, pp. 114280-114280
Open Access | Times Cited: 8
Hybrid ensemble soft computing approach for predicting penetration rate of tunnel boring machine in a rock environment
Abidhan Bardhan, Navid Kardani, Anasua GuhaRay, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2021) Vol. 13, Iss. 6, pp. 1398-1412
Open Access | Times Cited: 45
Novel Fuzzy-Based Optimization Approaches for the Prediction of Ultimate Axial Load of Circular Concrete-Filled Steel Tubes
Jin‐song Liao, Panagiotis G. Asteris, Liborio Cavaleri, et al.
Buildings (2021) Vol. 11, Iss. 12, pp. 629-629
Open Access | Times Cited: 44
A critical review of conventional and soft computing methods for slope stability analysis
Prithvendra Singh, Abidhan Bardhan, Fucheng Han, et al.
Modeling Earth Systems and Environment (2022) Vol. 9, Iss. 1, pp. 1-17
Closed Access | Times Cited: 31
Determining Seismic Bearing Capacity of Footings Embedded in Cohesive Soil Slopes Using Multivariate Adaptive Regression Splines
Van Qui Lai, Fengwen Lai, Dayu Yang, et al.
International Journal of Geosynthetics and Ground Engineering (2022) Vol. 8, Iss. 4
Open Access | Times Cited: 29
State of art soft computing based simulation models for bearing capacity of pile foundation: a comparative study of hybrid ANNs and conventional models
Manish Kumar, Vinay Kumar, Balaji Ganesh Rajagopal, et al.
Modeling Earth Systems and Environment (2022) Vol. 9, Iss. 2, pp. 2533-2551
Closed Access | Times Cited: 29
Estimation of California bearing ratio for hill highways using advanced hybrid artificial neural network algorithms
Ishwor Thapa, Sufyan Ghani
Multiscale and Multidisciplinary Modeling Experiments and Design (2023) Vol. 7, Iss. 2, pp. 1119-1144
Closed Access | Times Cited: 21
Soft computing-based prediction models for compressive strength of concrete
Manish Kumar, Rahul Biswas, Divesh Ranjan Kumar, et al.
Case Studies in Construction Materials (2023) Vol. 19, pp. e02321-e02321
Open Access | Times Cited: 19
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