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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:

Application of ensemble learning in predicting shallow foundation settlement in cohesionless soil
Ningthoujam Jibanchand, Konsam Rambha Devi
International Journal of Geotechnical Engineering (2023) Vol. 17, Iss. 3, pp. 234-245
Closed Access | Times Cited: 11

Showing 11 citing articles:

A systematic review and meta-analysis of artificial neural network, machine learning, deep learning, and ensemble learning approaches in field of geotechnical engineering
Elaheh Yaghoubi, Elnaz Yaghoubi, Ahmed A. Khamees, et al.
Neural Computing and Applications (2024) Vol. 36, Iss. 21, pp. 12655-12699
Open Access | Times Cited: 21
Bearing capacity prediction of open caissons in anisotropic clays utilizing a deep neural network coupled with a population based training approach
Wittaya Jitchaijaroen, Rungroad Suppakul, Mohammad Khajehzadeh, et al.
Results in Engineering (2025), pp. 104323-104323
Open Access | Times Cited: 1
AI-powered simulation models for estimating the consolidation settlement of shallow foundations
J. Jagan, Pijush Samui
Modeling Earth Systems and Environment (2024) Vol. 11, Iss. 1
Closed Access | Times Cited: 3
Assessment of leachate-contaminated clays using experimental and artificial methods
Hossein Moradi Moghaddam, Ahmad Fahimifar, Taghi Ebadi, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2024)
Open Access | Times Cited: 2
Sequential backward feature selection for optimizing permanent strain model of unbound aggregates
Samuel Olamide Aregbesola, Jongmuk Won, Seungjun Kim, et al.
Case Studies in Construction Materials (2023) Vol. 19, pp. e02554-e02554
Open Access | Times Cited: 5
Comparative Analysis of Ensemble Learning Approaches for Slope Stability Prediction
Saurabh Kumar Anuragi, D. Kishan, Sri Khetwat Saritha
International Journal of Civil Engineering (2024) Vol. 11, Iss. 5, pp. 168-180
Open Access | Times Cited: 1
Automated signal‐based evaluation of dynamic cone resistance via machine learning for subsurface characterization
Samuel Olamide Aregbesola, Yong‐Hoon Byun
Computer-Aided Civil and Infrastructure Engineering (2024) Vol. 39, Iss. 16, pp. 2541-2552
Open Access
Developing an effective optimized machine learning approaches for settlement prediction of shallow foundation
Mohammad Khajehzadeh, Suraparb Keawsawasvong, Viroon Kamchoom‬, et al.
Heliyon (2024) Vol. 10, Iss. 17, pp. e36714-e36714
Open Access
AI-Powered Simulation Models for Estimating the Consolidation Settlement of Shallow Foundations
J. Jagan, Pijush Samui
Research Square (Research Square) (2024)
Open Access
A hybrid learning approach for simulating settlement of shallow foundation
Jiaman Li, Jundong Wu, Wei Hu
Multiscale and Multidisciplinary Modeling Experiments and Design (2024) Vol. 8, Iss. 1
Closed Access
Machine learning models for predicting the bearing capacity of shallow foundations: A Comparative study and sensitivity analysis
Hamid Mohammadnezhad, Seyedmohammad Eslami
Numerical Methods in Civil Engineering (2024) Vol. 9, Iss. 2, pp. 40-53
Closed Access
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