Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Real-time prediction of shield moving trajectory during tunnelling
Shui‐Long Shen, Khalid Elbaz, Wafaa Mohamed Shaban, et al.
Acta Geotechnica (2022) Vol. 17, Iss. 4, pp. 1533-1549
Closed Access | Times Cited: 83

Showing 1-25 of 83 citing articles:

Ensemble learning framework for landslide susceptibility mapping: Different basic classifier and ensemble strategy
Taorui Zeng, Liyang Wu, Dario Peduto, et al.
Geoscience Frontiers (2023) Vol. 14, Iss. 6, pp. 101645-101645
Open Access | Times Cited: 75
Deep learning technologies for shield tunneling: Challenges and opportunities
Cheng Zhou, Yuyue Gao, Elton J. Chen, et al.
Automation in Construction (2023) Vol. 154, pp. 104982-104982
Closed Access | Times Cited: 54
A multi-stage data augmentation and AD-ResNet-based method for EPB utilization factor prediction
Honggan Yu, Hao Sun, Jianfeng Tao, et al.
Automation in Construction (2023) Vol. 147, pp. 104734-104734
Closed Access | Times Cited: 51
An optimized XGBoost-based machine learning method for predicting wave run-up on a sloping beach
Dede Tarwidi, Sri Redjeki Pudjaprasetya, Didit Adytia, et al.
MethodsX (2023) Vol. 10, pp. 102119-102119
Open Access | Times Cited: 49
Prevention/mitigation of natural disasters in urban areas
Jinchun Chai, Haoze Wu
Smart Construction and Sustainable Cities (2023) Vol. 1, Iss. 1
Open Access | Times Cited: 45
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
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
Assessment of safety status of shield tunnelling using operational parameters with enhanced SPA
Hai‐Min Lyu, Shui‐Long Shen, Annan Zhou, et al.
Tunnelling and Underground Space Technology (2022) Vol. 123, pp. 104428-104428
Closed Access | Times Cited: 41
Dynamic prediction for attitude and position of shield machine in tunneling: A hybrid deep learning method considering dual attention
Zeyu Dai, Peinan Li, Mengqi Zhu, et al.
Advanced Engineering Informatics (2023) Vol. 57, pp. 102032-102032
Closed Access | Times Cited: 28
Metro System Inundation in Zhengzhou, Henan Province, China
Hao Yang, Lin‐Shuang Zhao, Jun Chen
Sustainability (2022) Vol. 14, Iss. 15, pp. 9292-9292
Open Access | Times Cited: 32
Evaluation of spatial performance and supply-demand ratios of urban underground space based on POI data: A case study of Shanghai
Chen-Xiao Ma, Fang‐Le Peng
Tunnelling and Underground Space Technology (2022) Vol. 131, pp. 104775-104775
Open Access | Times Cited: 28
Application of an Optimized PSO-BP Neural Network to the Assessment and Prediction of Underground Coal Mine Safety Risk Factors
Dorcas Muadi Mulumba, Jiankang Liu, Jian Jun Hao, et al.
Applied Sciences (2023) Vol. 13, Iss. 9, pp. 5317-5317
Open Access | Times Cited: 21
Machine learning approach for predicting compressive strength in foam concrete under varying mix designs and curing periods
Soran Abdrahman Ahmad, Hemn Unis Ahmed, Serwan Rafiq, et al.
Smart Construction and Sustainable Cities (2023) Vol. 1, Iss. 1
Open Access | Times Cited: 21
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: 16
Optimizing Time-Series forecasting using stacked deep learning framework with enhanced adaptive moment estimation and error correction
Ravi Prakash Varshney, Dilip Kumar Sharma
Expert Systems with Applications (2024) Vol. 249, pp. 123487-123487
Closed Access | Times Cited: 6
TBM disc cutter wear prediction using stratal slicing and IPSO-LSTM in mixed weathered granite stratum
Deyun Mo, Liping Bai, Weiran Huang, et al.
Tunnelling and Underground Space Technology (2024) Vol. 148, pp. 105745-105745
Open Access | Times Cited: 5
Prediction of shield machine attitude parameters based on decomposition and multi-head attention mechanism
Qiushi Wang, Wenqi Ding, Kourosh Khoshelham, et al.
Automation in Construction (2025) Vol. 171, pp. 105973-105973
Closed Access
Probabilistic performance analysis of longitudinal tunnels based on coupled characterization of stratigraphic and geo-properties uncertainties
Chao Zhao, Wenping Gong, C. Hsein Juang, et al.
Tunnelling and Underground Space Technology (2025) Vol. 161, pp. 106552-106552
Closed Access
Characteristics and failure analysis of a railway tunnel collapse influenced by cavity in phyllite strata
Longlong Chen, Zhifeng Wang, Yaqiong Wang, et al.
Engineering Failure Analysis (2022) Vol. 142, pp. 106794-106794
Closed Access | Times Cited: 25
Base resistance of super-large and long piles in soft soil: performance of artificial neural network model and field implications
Quoc Thien Huynh, Thanh Trung Nguyen, Hoang Nguyen
Acta Geotechnica (2022) Vol. 18, Iss. 5, pp. 2755-2775
Open Access | Times Cited: 23
Interpretable predictive model for shield attitude control performance based on XGboost and SHAP
Min Hu, Haolan Zhang, Bingjian Wu, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 22
Development and application of a novel probabilistic back-analysis framework for geotechnical parameters in shield tunneling based on the surrogate model and Bayesian theory
Quansheng Liu, Yiming Lei, Xin Yin, et al.
Acta Geotechnica (2023) Vol. 18, Iss. 9, pp. 4899-4921
Closed Access | Times Cited: 15
Data-driven predictions of shield attitudes using Bayesian machine learning
Lai Wang, Qiujing Pan, Shuying Wang
Computers and Geotechnics (2023) Vol. 166, pp. 106002-106002
Closed Access | Times Cited: 13
A unified empirical method for predicting both vertical and horizontal ground displacements induced by tunnel excavation
Qingtao Lin, Meng Xu, Dechun Lu, et al.
Canadian Geotechnical Journal (2024) Vol. 61, Iss. 7, pp. 1468-1495
Closed Access | Times Cited: 4
Data-Based postural prediction of shield tunneling via machine learning with physical information
Jiaqi Chang, Hongwei Huang, Markus Thewes, et al.
Computers and Geotechnics (2024) Vol. 174, pp. 106584-106584
Closed Access | Times Cited: 4
Page 1 - Next Page

Scroll to top