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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 artificial intelligence in geotechnical engineering: A state-of-the-art review
Abolfazl Baghbani, Tanveer Choudhury, Susanga Costa, et al.
Earth-Science Reviews (2022) Vol. 228, pp. 103991-103991
Closed Access | Times Cited: 184

Showing 51-75 of 184 citing articles:

Predicting the strength of recycled glass powder-based geopolymers for improving mechanical behavior of clay soils using artificial intelligence
A. Baghbani
Materials research proceedings (2023) Vol. 31, pp. 646-655
Open Access | Times Cited: 11
Deep Learning Approach on Prediction of Soil Consolidation Characteristics
Mintae Kim, Muharrem A. Senturk, Rabia Korkmaz Tan, et al.
Buildings (2024) Vol. 14, Iss. 2, pp. 450-450
Open Access | Times Cited: 4
Prediction of the Unconfined Compressive Strength of Salinized Frozen Soil Based on Machine Learning
Huiwei Zhao, Bing Hui
Buildings (2024) Vol. 14, Iss. 3, pp. 641-641
Open Access | Times Cited: 4
Predicting the strut forces of the steel supporting structure of deep excavation considering various factors by machine learning methods
Haibo Hu, Xunjian Hu, Xiaonan Gong
Underground Space (2024) Vol. 18, pp. 114-129
Open Access | Times Cited: 4
The effectiveness of data pre-processing methods on the performance of machine learning techniques using RF, SVR, Cubist and SGB: a study on undrained shear strength prediction
Selçuk Demir, Emrehan Kutluğ Şahin
Stochastic Environmental Research and Risk Assessment (2024) Vol. 38, Iss. 8, pp. 3273-3290
Open Access | Times Cited: 4
Failure and post-failure kinematic disaster processes of columnar rock masses based on 3D discontinuous deformation analysis
Ke Ma, Shengze Zhao, Guoyang Liu, et al.
International Journal of Rock Mechanics and Mining Sciences (2024) Vol. 186, pp. 106003-106003
Closed Access | Times Cited: 4
Prediction of active length of pipes and tunnels under normal faulting with XGBoost integrating a complexity-performance balanced optimization approach
Tianjian Cheng, Chaofan Yao, Jingnan Duan, et al.
Computers and Geotechnics (2025) Vol. 179, pp. 107048-107048
Closed Access
Neural network coupled with nature-inspired optimization algorithms for prediction of microstructural and mechanical properties of nano-silica treated fine-grained soil
Ishwor Thapa, Sufyan Ghani, Panagiotis G. Asteris
Modeling Earth Systems and Environment (2025) Vol. 11, Iss. 1
Closed Access
Utilization of Generative Artificial Intelligence in Geotechnical and Geoenvironmental Engineering
Krishna R. Reddy, Jagadeesh Kumar Janga
Lecture notes in civil engineering (2025), pp. 241-267
Closed Access
Prediction of Member Forces of Steel Tubes on the Basis of a Sensor System with the Use of AI
Haiyu Li, Heung‐Jin Chung
Sensors (2025) Vol. 25, Iss. 3, pp. 919-919
Open Access
Augmented intelligence framework for real-time ground assessment under significant uncertainty
Javad Ghorbani, Sougol Aghdasi, Majidreza Nazem, et al.
Engineering With Computers (2025)
Open Access
Application of generative AI to automate numerical analysis and synthetic data generation in geotechnical engineering
Ali Parsa-Pajouh
(2025) Vol. 1, Iss. 1, pp. 46-55
Closed Access
Research on Slope Stability Prediction Based on MC-BKA-MLP Mixed Model
Yan Lu, Hongze Zhao
Applied Sciences (2025) Vol. 15, Iss. 6, pp. 3158-3158
Open Access
Research on Uncertainty of Landslide Susceptibility Prediction—Bibliometrics and Knowledge Graph Analysis
Zhengli Yang, Chao Liu, Ruihua Nie, et al.
Remote Sensing (2022) Vol. 14, Iss. 16, pp. 3879-3879
Open Access | Times Cited: 16
Using time series analysis and dual-stage attention-based recurrent neural network to predict landslide displacement
Dongxin Bai, Guangyin Lu, Z. Q. Zhu, et al.
Environmental Earth Sciences (2022) Vol. 81, Iss. 21
Closed Access | Times Cited: 16
Probabilistic machine learning for predicting desiccation cracks in clayey soils
Babak Jamhiri, Yongfu Xu, Mahdi Shadabfar, et al.
Bulletin of Engineering Geology and the Environment (2023) Vol. 82, Iss. 9
Closed Access | Times Cited: 10
Machine learning models for predicting rock fracture toughness at different temperature conditions
Xunjian Hu, Dong Liao, Dongdong Ma, et al.
Case Studies in Construction Materials (2023) Vol. 19, pp. e02622-e02622
Open Access | Times Cited: 10
Leading-edge Artificial Intelligence (AI) and Internet of Things (IoT) technologies for enhanced geotechnical site characterization
Nitin Liladhar Rane, Saurabh Choudhary, Jayesh Rane
SSRN Electronic Journal (2023)
Closed Access | Times Cited: 10
Artificial intelligence in tunnel construction: A comprehensive review of hotspots and frontier topics
Lianbaichao Liu, Zhanping Song, Xu Li
Geohazard Mechanics (2023) Vol. 2, Iss. 1, pp. 1-12
Open Access | Times Cited: 10
A framework coupled neural networks and SPH depth integrated model for landslide propagation warning
Lingang Gao, Manuel Pastor, Tongchun Li, et al.
Acta Geotechnica (2023) Vol. 18, Iss. 7, pp. 3863-3888
Closed Access | Times Cited: 9
Artificial Neural Network model to predict the dynamic properties of sand-polyurethane composite materials for GSI applications
Michele Placido Antonio Gatto, Lorella Montrasio
Soil Dynamics and Earthquake Engineering (2023) Vol. 172, pp. 108032-108032
Open Access | Times Cited: 9
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
Artificial intelligence-based prediction of geotechnical impacts of polyethylene bottles and polypropylene on clayey soil
A. Baghbani
Materials research proceedings (2023) Vol. 31, pp. 734-744
Open Access | Times Cited: 9
Prediction of collapsibility of loess site based on artificial intelligence: comparison of different algorithms
Xueliang Zhu, Shuai Shao, Shengjun Shao
Environmental Earth Sciences (2024) Vol. 83, Iss. 3
Closed Access | Times Cited: 3
Comprehensive review of AI and ML tools for earthquake damage assessment and retrofitting strategies
P. K. S. Bhadauria
Earth Science Informatics (2024) Vol. 17, Iss. 5, pp. 3945-3962
Closed Access | Times Cited: 3

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