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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:

State-of-the-art review of geotechnical-driven artificial intelligence techniques in underground soil-structure interaction
S.C. Jong, Dominic Ek Leong Ong, Erwin Oh
Tunnelling and Underground Space Technology (2021) Vol. 113, pp. 103946-103946
Closed Access | Times Cited: 112

Showing 1-25 of 112 citing articles:

Future of machine learning in geotechnics
Kok‐Kwang Phoon, Wengang Zhang
Georisk Assessment and Management of Risk for Engineered Systems and Geohazards (2022) Vol. 17, Iss. 1, pp. 7-22
Closed Access | Times Cited: 156
Prediction of geological characteristics from shield operational parameters by integrating grid search and K-fold cross validation into stacking classification algorithm
Tao Yan, Shui‐Long Shen, Annan Zhou, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2022) Vol. 14, Iss. 4, pp. 1292-1303
Closed Access | Times Cited: 100
Investigation of feature contribution to shield tunneling-induced settlement using Shapley additive explanations method
K. K. Pabodha M. Kannangara, Wan‐Huan Zhou, Zhi Ding, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2022) Vol. 14, Iss. 4, pp. 1052-1063
Open Access | Times Cited: 94
Comparison of neural network, Gaussian regression, support vector machine, long short-term memory, multi-gene genetic programming, and M5 Trees methods for solving civil engineering problems
Erdal Uncuoğlu, Hatice Çıtakoğlu, Levent Latifoğlu, et al.
Applied Soft Computing (2022) Vol. 129, pp. 109623-109623
Closed Access | Times Cited: 79
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: 19
Prediction of dynamic shear modulus of saturated coral sand based on explainable artificial intelligence
Bin Ruan, Guo Yang, Zhenglong Zhou, et al.
Construction and Building Materials (2025) Vol. 461, pp. 139878-139878
Closed Access | Times Cited: 2
Tunnel boring machine vibration-based deep learning for the ground identification of working faces
Mengbo Liu, Shaoming Liao, Yifeng Yang, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2021) Vol. 13, Iss. 6, pp. 1340-1357
Open Access | Times Cited: 71
Real-time prediction of shield moving trajectory during tunnelling using GRU deep neural network
Nan Zhang, Ning Zhang, Qian Zheng, et al.
Acta Geotechnica (2021) Vol. 17, Iss. 4, pp. 1167-1182
Closed Access | Times Cited: 67
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 wall deflection induced by braced excavation in spatially variable soils via convolutional neural network
Chongzhi Wu, Li Hong, Lin Wang, et al.
Gondwana Research (2022) Vol. 123, pp. 184-197
Closed Access | Times Cited: 64
Unconfined compressive strength of MICP and EICP treated sands subjected to cycles of wetting-drying, freezing-thawing and elevated temperature: Experimental and EPR modelling
Isaac Ahenkorah, Md Mizanur Rahman, Md Rajibul Karim, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2022) Vol. 15, Iss. 5, pp. 1226-1247
Open Access | Times Cited: 51
Auto machine learning-based modelling and prediction of excavation-induced tunnel displacement
Dongmei Zhang, Yiming Shen, Zhongkai Huang, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2022) Vol. 14, Iss. 4, pp. 1100-1114
Open Access | Times Cited: 50
Novel hybrid MFO-XGBoost model for predicting the racking ratio of the rectangular tunnels subjected to seismic loading
Van-Quang Nguyen, Viet‐Linh Tran, Duy-Duan Nguyen, et al.
Transportation Geotechnics (2022) Vol. 37, pp. 100878-100878
Closed Access | Times Cited: 38
Dynamic and explainable deep learning-based risk prediction on adjacent building induced by deep excavation
Xuyang Li, Yue Pan, Limao Zhang, et al.
Tunnelling and Underground Space Technology (2023) Vol. 140, pp. 105243-105243
Closed Access | Times Cited: 29
Development of urban underground space in coastal cities in China: A review
Peng Yu, Honghua Liu, Zhongsheng Wang, et al.
Deep Underground Science and Engineering (2023) Vol. 2, Iss. 2, pp. 148-172
Open Access | Times Cited: 27
AI and machine learning for soil analysis: an assessment of sustainable agricultural practices
Muhammad Awais, Syed Muhammad Zaigham Abbas Naqvi, Hao Zhang, et al.
Bioresources and Bioprocessing (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 23
TBM performance prediction using LSTM-based hybrid neural network model: Case study of Baimang River tunnel project in Shenzhen, China
Qihang Xu, Xin Huang, Baogang Zhang, et al.
Underground Space (2023) Vol. 11, pp. 130-152
Open Access | Times Cited: 22
Machine learning-based soil–structure interaction analysis of laterally loaded piles through physics-informed neural networks
Weihang Ouyang, Guanhua Li, Liang Chen, et al.
Acta Geotechnica (2024) Vol. 19, Iss. 7, pp. 4765-4790
Closed Access | Times Cited: 14
Effect and control of foundation pit excavation on existing tunnels: A state-of-the-art review
Bo Liu, Wenwen Wu, Haipei Lu, et al.
Tunnelling and Underground Space Technology (2024) Vol. 147, pp. 105704-105704
Closed Access | Times Cited: 10
Artificial Intelligence in Agricultural Mapping: A Review
Ramón Espinel, Gricelda Herrera-Franco, José Luis Rivadeneira García, et al.
Agriculture (2024) Vol. 14, Iss. 7, pp. 1071-1071
Open Access | Times Cited: 10
A novel Bayesian network approach for predicting soil-structure interactions induced by deep excavations
S.C. Jong, Dominic Ek Leong Ong
Tunnelling and Underground Space Technology (2024) Vol. 152, pp. 105865-105865
Open Access | Times Cited: 7
Application of KNN-based isometric mapping and fuzzy c-means algorithm to predict short-term rockburst risk in deep underground projects
Muhammad Kamran, Barkat Ullah, Mahmood Ahmad, et al.
Frontiers in Public Health (2022) Vol. 10
Open Access | Times Cited: 36
Prediction of UCS and CBR behavior of fiber-reinforced municipal solid waste incinerator bottom ash composites using experimental and machine learning methods
Sanjeev Kumar, Davinder Singh
Construction and Building Materials (2022) Vol. 367, pp. 130230-130230
Closed Access | Times Cited: 30
Review of machine learning application in mine blasting
Ahmed Abd Elwahab, Erkan Topal, Hyongdoo Jang
Arabian Journal of Geosciences (2023) Vol. 16, Iss. 2
Open Access | Times Cited: 17
A Bayesian inference framework for geomaterial characterization and evaluation of complex soil-structure interactions
S.C. Jong, Dominic Ek Leong Ong
Computers and Geotechnics (2024) Vol. 172, pp. 106452-106452
Open Access | Times Cited: 6
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