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:

Real-time hard-rock tunnel prediction model for rock mass classification using CatBoost integrated with Sequential Model-Based Optimization
Yin Bo, Quansheng Liu, Xing Huang, et al.
Tunnelling and Underground Space Technology (2022) Vol. 124, pp. 104448-104448
Closed Access | Times Cited: 81

Showing 1-25 of 81 citing articles:

Time series prediction of tunnel boring machine (TBM) performance during excavation using causal explainable artificial intelligence (CX-AI)
Kunyu Wang, Limao Zhang, Xianlei Fu
Automation in Construction (2023) Vol. 147, pp. 104730-104730
Closed Access | Times Cited: 42

Feedback on a shared big dataset for intelligent TBM Part I: Feature extraction and machine learning methods
Jianbin Li, Zuyu Chen, Xu Li, et al.
Underground Space (2023) Vol. 11, pp. 1-25
Open Access | Times Cited: 42

Multisource information fusion for real-time prediction and multiobjective optimization of large-diameter slurry shield attitude
Xianguo Wu, Jingyi Wang, Zongbao Feng, et al.
Reliability Engineering & System Safety (2024) Vol. 250, pp. 110305-110305
Closed Access | Times Cited: 15

Feature fusion method for rock mass classification prediction and interpretable analysis based on TBM operating and cutter wear data
Wen‐Kun Yang, Zuyu Chen, Haitao Zhao, et al.
Tunnelling and Underground Space Technology (2025) Vol. 157, pp. 106351-106351
Closed Access | Times Cited: 1

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

Machine learning models to predict the tunnel wall convergence
Jian Zhou, Yuxin Chen, Chuanqi Li, et al.
Transportation Geotechnics (2023) Vol. 41, pp. 101022-101022
Closed Access | Times Cited: 31

Estimating locations of soil–rock interfaces based on vibration data during shield tunnelling
Shui‐Long Shen, Tao Yan, Annan Zhou
Automation in Construction (2023) Vol. 150, pp. 104813-104813
Closed Access | Times Cited: 29

Soft ground tunnel lithology classification using clustering-guided light gradient boosting machine
Kürşat Kiliç, Hajime Ikeda, Tsuyoshi Adachi, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2023) Vol. 15, Iss. 11, pp. 2857-2867
Open Access | Times Cited: 25

Prediction of tunnel deformation using PSO variant integrated with XGBoost and its TBM jamming application
Yin Bo, Xiaogang Guo, Quansheng Liu, et al.
Tunnelling and Underground Space Technology (2024) Vol. 150, pp. 105842-105842
Closed Access | Times Cited: 14

Decision Intelligence-Based Predictive Modelling of Hard Rock Pillar Stability Using K-Nearest Neighbour Coupled with Grey Wolf Optimization Algorithm
Muhammad Kamran, Waseem Chaudhry, Blessing Olamide Taiwo, et al.
Processes (2024) Vol. 12, Iss. 4, pp. 783-783
Open Access | Times Cited: 13

Real-time classification model for tunnel surrounding rocks based on high-resolution neural network and structure–optimizer hyperparameter optimization
Junjie Ma, Chunchi Ma, Tianbin Li, et al.
Computers and Geotechnics (2024) Vol. 168, pp. 106155-106155
Closed Access | Times Cited: 9

Dynamic prediction and optimization of tunneling parameters with high reliability based on a hybrid intelligent algorithm
Hongyu Chen, Qiping Geoffrey Shen, Mirosław J. Skibniewski, et al.
Information Fusion (2024), pp. 102705-102705
Closed Access | Times Cited: 9

Data-driven real-time advanced geological prediction in tunnel construction using a hybrid deep learning approach
Xianlei Fu, Maozhi Wu, Robert L. K. Tiong, et al.
Automation in Construction (2022) Vol. 146, pp. 104672-104672
Closed Access | Times Cited: 35

Robust model for tunnel squeezing using Bayesian optimized classifiers with partially missing database
Yin Bo, Xing Huang, Yucong Pan, et al.
Underground Space (2023) Vol. 10, pp. 91-117
Open Access | Times Cited: 20

An intelligent method for TBM surrounding rock classification based on time series segmentation of rock-machine interaction data
Yadong Xue, Wei Luo, Liang Chen, et al.
Tunnelling and Underground Space Technology (2023) Vol. 140, pp. 105317-105317
Closed Access | Times Cited: 18

Composite interpretability optimization ensemble learning inversion surrounding rock mechanical parameters and support optimization in soft rock tunnels
Jingqi Cui, Shunchuan Wu, Haiyong Cheng, et al.
Computers and Geotechnics (2023) Vol. 165, pp. 105877-105877
Open Access | Times Cited: 18

BILSTM-Based Deep Neural Network for Rock-Mass Classification Prediction Using Depth-Sequence MWD Data: A Case Study of a Tunnel in Yunnan, China
Xu Cheng, Hua Tang, Zhenjun Wu, et al.
Applied Sciences (2023) Vol. 13, Iss. 10, pp. 6050-6050
Open Access | Times Cited: 17

Estimating the penetration rate of tunnel boring machines via gradient boosting algorithms
Ebrahim Ghorbani, Saffet Yağız
Engineering Applications of Artificial Intelligence (2024) Vol. 136, pp. 108985-108985
Closed Access | Times Cited: 7

Predictive slope stability early warning model based on CatBoost
Yuanli Cai, Ying Yuan, Aihong Zhou
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 6

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

Novel multifractal-based classification model for the quality grades of surrounding rock within tunnels
Junjie Ma, Tianbin Li, Zheng Zhang, et al.
Underground Space (2024) Vol. 20, pp. 140-156
Closed Access | Times Cited: 5

A machine learning approach for prediction of reverse solute flux in forward osmosis
Ibrar Ibrar, Sudesh Yadav, Ali Altaee, et al.
Journal of Water Process Engineering (2023) Vol. 54, pp. 103956-103956
Closed Access | Times Cited: 15

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

Capacity Estimation for Lithium-ion Batteries Based on Impedance Spectral Dynamics and Deep Gaussian Process
Shude Zhang, Weiru Yuan, Yingzhou Wang, et al.
IEEE Transactions on Power Electronics (2024) Vol. 39, Iss. 8, pp. 10287-10298
Closed Access | Times Cited: 4

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