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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:

Random forest-based predictors for driving forces of earth pressure balance (EPB) shield tunnel boring machine (TBM)
Xiangxun Kong, Xianzhang Ling, Liang Tang, et al.
Tunnelling and Underground Space Technology (2022) Vol. 122, pp. 104373-104373
Closed Access | Times Cited: 54

Showing 1-25 of 54 citing articles:

A multi-channel decoupled deep neural network for tunnel boring machine torque and thrust prediction
Honggan Yu, Chengjin Qin, Jianfeng Tao, et al.
Tunnelling and Underground Space Technology (2023) Vol. 133, pp. 104949-104949
Closed Access | Times Cited: 47
Deep reinforcement learning approach to optimize the driving performance of shield tunnelling machines
Khalid Elbaz, Annan Zhou, Shui‐Long Shen
Tunnelling and Underground Space Technology (2023) Vol. 136, pp. 105104-105104
Closed Access | Times Cited: 40
Data-driven joint multiobjective prediction and optimization for tunnel-induced adjacent bridge pier displacement: A case study in China
Hongyu Chen, Jun Liu, Yawei Qin, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 142, pp. 109616-109616
Closed Access | Times Cited: 1
Attitude-Predictive Control of Large-Diameter Shield Tunneling: PCA-SVR Machine Learning Algorithm Application in a Case Study of the Zhuhai Xingye Express Tunnel
Hui Li, Yijun Tan, Decheng Zeng, et al.
Applied Sciences (2025) Vol. 15, Iss. 4, pp. 1880-1880
Open Access | Times Cited: 1
Unfavorable geology recognition in front of shallow tunnel face using machine learning
Chenyang Zhao, Elham Mahmoudi, Maomao Luo, et al.
Computers and Geotechnics (2023) Vol. 157, pp. 105313-105313
Closed Access | Times Cited: 26
Multi-status Bayesian network for analyzing collapse risk of excavation construction
Song-Shun Lin, Annan Zhou, Shui‐Long Shen
Automation in Construction (2023) Vol. 158, pp. 105193-105193
Closed Access | Times Cited: 22
Safety evaluation of buildings adjacent to shield construction in karst areas: An improved extension cloud approach
Hongyu Chen, Sai Yang, Zongbao Feng, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 124, pp. 106386-106386
Closed Access | Times Cited: 21
Machine learning–informed soil conditioning for mechanized shield tunneling
Shuying Wang, Xiao Yuan, Tongming Qu
Computer-Aided Civil and Infrastructure Engineering (2024) Vol. 39, Iss. 17, pp. 2662-2682
Closed Access | Times Cited: 7
Autonomous steering control for tunnel boring machines
Zhe Zheng, Kaidi Luo, X.-L. Tan, et al.
Automation in Construction (2024) Vol. 159, pp. 105259-105259
Closed Access | Times Cited: 5
Subgrade settlements of existing railway lines and operational parameters of shield machine induced by twin shield tunnel excavations: A case study
Xiang Liu, Rui Zhang, Qian Fang, et al.
Journal of Central South University (2024) Vol. 31, Iss. 1, pp. 272-287
Closed Access | Times Cited: 5
Deep learning characterization of rock conditions based on tunnel boring machine data
Xu Li, Min Yao, Jidong Yuan, et al.
Underground Space (2023) Vol. 12, pp. 89-101
Open Access | Times Cited: 13
A novel workflow including denoising and hybrid deep learning model for shield tunneling construction parameter prediction
Yuxian Zhang, Xuhua Ren, Jixun Zhang, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108103-108103
Closed Access | Times Cited: 5
Indirect Evaluation of the Influence of Rock Boulders in Blasting to the Geohazard: Unearthing Geologic Insights Fused with Tree Seed based LSTM Algorithm
Blessing Olamide Taiwo, Shahab Hosseini, Yewuhalashet Fissha, et al.
Geohazard Mechanics (2024)
Open Access | Times Cited: 5
TBM tunneling strata automatic identification and working conditions decision support
Kang Fu, Daohong Qiu, Yiguo Xue, et al.
Automation in Construction (2024) Vol. 163, pp. 105425-105425
Closed Access | Times Cited: 4
A Quality Index for Construction Big Data in Shield Tunneling
Chao Zhang, Yuhao Ren, Q. Huang, et al.
(2025)
Closed Access
A Novel Real-Time Torque Prediction of EPB Shield in Mixed Ground Using Machine Learning Method Based on Geological Knowledge Fusion
Tsunming Wong, Yingjie Wei, Yong Zeng, et al.
Journal of Construction Engineering and Management (2025) Vol. 151, Iss. 3
Closed Access
Thrust force requirement prediction using HOA‐XGBoost for TBM tunneling in squeezing ground
Rongwen Chen, Minglin Zheng, Fulin Li, et al.
ce/papers (2025) Vol. 8, Iss. 2, pp. 1439-1447
Closed Access
Real-time prediction of attitude and moving trajectory in shield tunneling based optimal input parameter combination using random forest deep learning method
Xiang Shen, Xiangsheng Chen, Xiaohua Bao, et al.
Acta Geotechnica (2023) Vol. 18, Iss. 12, pp. 6687-6707
Closed Access | Times Cited: 12
Prediction of ground subsidence by shield tunneling using ensemble learning
Dukun Zhao, Zhangang Sun, Yueji He, et al.
Tunnelling and Underground Space Technology (2023) Vol. 141, pp. 105343-105343
Closed Access | Times Cited: 12
A novel decomposition and hybrid transfer learning-based method for multi-step cutterhead torque prediction of shield machine
Gang Shi, Chengjin Qin, Zhinan Zhang, et al.
Mechanical Systems and Signal Processing (2024) Vol. 214, pp. 111362-111362
Closed Access | Times Cited: 3
Model test on cutterhead-soil interaction during shield tunneling and its theoretical model
Xiang Shen, Dajun Yuan, Dalong Jin, et al.
Underground Space (2024) Vol. 20, pp. 46-68
Open Access | Times Cited: 3
Forecasting Face Support Pressure During EPB Shield Tunneling in Soft Ground Formations Using Support Vector Regression and Meta-heuristic Optimization Algorithms
Arsalan Mahmoodzadeh, Hamid Reza Nejati, Mokhtar Mohammadi, et al.
Rock Mechanics and Rock Engineering (2022) Vol. 55, Iss. 10, pp. 6367-6386
Closed Access | Times Cited: 14
Deep Learning Method on Deformation Prediction for Large-Section Tunnels
Wei Xu, Ming Cheng, Xiangyang Xu, et al.
Symmetry (2022) Vol. 14, Iss. 10, pp. 2019-2019
Open Access | Times Cited: 14
Reinforcement learning-based optimizer to improve the steering of shield tunneling machine
Khalid Elbaz, Shui‐Long Shen, Annan Zhou, et al.
Acta Geotechnica (2023) Vol. 19, Iss. 6, pp. 4167-4187
Closed Access | Times Cited: 8
Point and interval estimation of rock mass boreability for tunnel boring machine using an improved attribute-weighted deep belief network
Xin Yin, Xing Huang, Yucong Pan, et al.
Acta Geotechnica (2022) Vol. 18, Iss. 4, pp. 1769-1791
Closed Access | Times Cited: 12
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