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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:

Modelling the performance of EPB shield tunnelling using machine and deep learning algorithms
Song-Shun Lin, Shui‐Long Shen, Ning Zhang, et al.
Geoscience Frontiers (2021) Vol. 12, Iss. 5, pp. 101177-101177
Open Access | Times Cited: 80

Showing 26-50 of 80 citing articles:

Applications of Machine Learning in Mechanised Tunnel Construction: A Systematic Review
Feng Shan, Xuzhen He, Haoding Xu, et al.
Eng—Advances in Engineering (2023) Vol. 4, Iss. 2, pp. 1516-1535
Open Access | Times Cited: 18
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: 7
Prediction of Shield Machine Attitude Based on Various Artificial Intelligence Technologies
Haohan Xiao, Bo Xing, Yujie Wang, et al.
Applied Sciences (2021) Vol. 11, Iss. 21, pp. 10264-10264
Open Access | Times Cited: 40
Enhancing earth pressure balance tunnel boring machine performance with support vector regression and particle swarm optimization
Hongjie Yu, Xu Zhou, Xiaoli Zhang, et al.
Automation in Construction (2022) Vol. 142, pp. 104457-104457
Closed Access | Times Cited: 25
Modeling the Mechanical Response of Cement-Admixed Clay Under Different Stress Paths Using Recurrent Neural Networks
Chana Phutthananon, Praiya Ratanakijkul, Sompote Youwai, et al.
International Journal of Geosynthetics and Ground Engineering (2024) Vol. 10, Iss. 2
Closed Access | Times Cited: 6
Predicting longitudinal tunnel deformation due to deep excavation-induced ground movement
Linlong Mu, Peiyun Zhang, Zhenhao Shi, et al.
Tunnelling and Underground Space Technology (2022) Vol. 131, pp. 104793-104793
Closed Access | Times Cited: 22
Shield machine position prediction and anomaly detection during tunnelling in loess region using ensemble and deep learning algorithms
Xuedong Bai, Wen-Chieh Cheng, Bin Wu, et al.
Acta Geotechnica (2023) Vol. 18, Iss. 11, pp. 6175-6199
Closed Access | Times Cited: 12
Data-driven real-time prediction for attitude and position of super-large diameter shield using a hybrid deep learning approach
Yanbin Fu, Lei Chen, Hao Xiong, et al.
Underground Space (2023) Vol. 15, pp. 275-297
Open Access | Times Cited: 12
Improving Soil Stability with Alum Sludge: An AI-Enabled Approach for Accurate Prediction of California Bearing Ratio
Abolfazl Baghbani, Minh Duc Nguyen, Ali Alnedawi, et al.
(2023)
Open Access | Times Cited: 11
A novel Bi-LSTM method fusing current and historical data for tunnelling parameters of shield tunnel
Dechun Lu, Yihan Liu, Fanchao Kong, et al.
Transportation Geotechnics (2024), pp. 101402-101402
Closed Access | Times Cited: 4
An extended TODIM-based model for evaluating risks of excavation system
Song-Shun Lin, Shui‐Long Shen, Ning Zhang, et al.
Acta Geotechnica (2021) Vol. 17, Iss. 4, pp. 1053-1069
Closed Access | Times Cited: 25
Improving Soil Stability with Alum Sludge: An AI-Enabled Approach for Accurate Prediction of California Bearing Ratio
Abolfazl Baghbani, Minh Duc Nguyen, Ali Alnedawi, et al.
Applied Sciences (2023) Vol. 13, Iss. 8, pp. 4934-4934
Open Access | Times Cited: 11
High-precision cutterhead torque prediction for tunnel boring machines using an attention-based embedded LSTM neural network
Yi Qin, Jianghong Zhou, Dengyu Xiao, et al.
Measurement (2023) Vol. 224, pp. 113888-113888
Closed Access | Times Cited: 10
Intelligent decision on shield construction parameters based on safety evaluation model and sparrow search algorithm
Wei Gao, Shuangshuang Ge, Shuang Cui, et al.
Reliability Engineering & System Safety (2025), pp. 110973-110973
Closed Access
Analytical solution of the evolution of railway subgrade settlement induced by shield tunnelling beneath considering soil stress release
Yao Shan, Guankai Wang, Weifan Lin, et al.
Tunnelling and Underground Space Technology (2025) Vol. 162, pp. 106607-106607
Closed Access
An innovative GWO-BiLSTM model for predicting the advance rates of double-line subway shield tunneling with TBM
Jianfei Pan, Hang Lin, J. Wu, et al.
Archives of Civil and Mechanical Engineering (2025) Vol. 25, Iss. 3
Closed Access
A lightweight physics‐data‐driven method for real‐time prediction of subgrade settlements induced by shield tunneling
Guankai Wang, Shan Yao, Weifan Lin, et al.
Computer-Aided Civil and Infrastructure Engineering (2025)
Open Access
Ensemble model for risk status evaluation of excavation
Song-Shun Lin, Shui‐Long Shen, Annan Zhou, et al.
Automation in Construction (2021) Vol. 132, pp. 103943-103943
Closed Access | Times Cited: 21
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: 15
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: 15
Real-time early warning and the prediction of air pollutants for sustainable development in smart cities
Wafaa Mohamed Shaban, Xie Dongxi, Kariman Samir Daef, et al.
Atmospheric Pollution Research (2024) Vol. 15, Iss. 7, pp. 102162-102162
Closed Access | Times Cited: 3
System reliability-based robust design of deep foundation pit considering multiple failure modes
Li Hong, Xiangyu Wang, Wengang Zhang, et al.
Geoscience Frontiers (2023) Vol. 15, Iss. 2, pp. 101761-101761
Open Access | Times Cited: 8
An integrated framework for improving the efficiency and safety of hydraulic tunnel construction
Yuxian Zhang, Jixun Zhang, Changsheng Wang, et al.
Tunnelling and Underground Space Technology (2022) Vol. 131, pp. 104836-104836
Closed Access | Times Cited: 12
Characteristics, numerical analysis and countermeasures of mud inrush geohazards of Mountain tunnel in karst region
Longlong Chen, Zhifeng Wang, Wu Zhang, et al.
Geomatics Natural Hazards and Risk (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 7
Dynamic prediction of moving trajectory in pipe jacking: GRU-based deep learning framework
Yifeng Yang, Shaoming Liao, Mengbo Liu
Frontiers of Structural and Civil Engineering (2023) Vol. 17, Iss. 7, pp. 994-1010
Closed Access | Times Cited: 7

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