Enhancing Mine Blasting Safety: Developing Intelligent Systems for Accurate Flyrock Prediction through Optimized Group Method of Data Handling Methods DOI
Xiaohua Ding, Mahdi Hasanipanah, Masoud Monjezi

et al.

Natural Resources Research, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 21, 2024

Language: Английский

Physics-informed explainable encoder-decoder deep learning for predictive estimation of building carbon emissions DOI
Chao Chen, Limao Zhang, Cheng Zhou

et al.

Renewable and Sustainable Energy Reviews, Journal Year: 2025, Volume and Issue: 213, P. 115478 - 115478

Published: Feb. 17, 2025

Language: Английский

Citations

2
A Visual Survey of Tunnel Boring Machine (TBM) Performance in Tunneling Excavation: Mainstream Direction, Brief Review and Future Prospects DOI Creative Commons
Yulin Zhang, Jian Zhou,

Yingui Qiu

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(11), P. 4512 - 4512

Published: May 24, 2024

This study employs scientometric analysis to investigate the current trajectory of research on tunnel boring machine (TBM) performance and collaborative efforts. Utilizing software tools like Pajek 5.16 VOSviewer 1.6.18, it scrutinizes literature from 2000 2021 sourced Web Science (WOS). The findings illuminate TBM as an interdisciplinary intersectoral field attracting increasing national institutional attention. Notable contributions China, Iran, United States, Turkey, Australia underscore global significance research. recent upsurge in annual publications, primarily driven by Chinese initiatives, reflects a renewed vigor exploration. Additionally, paper presents succinct evaluation advantages drawbacks compared conventional drill blast methods, discussing key considerations excavation methodology selection. Moreover, comprehensively reviews prediction models, categorizing them into theoretical, empirical, artificial intelligence-driven approaches. Finally, rooted metaverse theory, discourse delves immersive learning model architecture metaverse. In future, training diagram can be employed scenarios such employee promotion safety knowledge. simulate, monitor, diagnose, predict, control organization, management, service processes behaviors TBMs. will enhance efficient collaboration across various aspects project production cycle. forward-looking perspective anticipates future trends technology, emphasizing societal impact enhancement economic benefits.

Language: Английский

Citations

8
Comprehensive review and future perspectives on prediction and mitigation of tunnel-induced ground settlement: A bibliometric analysis and methodological overview (2002–2022) DOI Creative Commons
Jian Zhou, Hongning Qi, Kang Peng

et al.

Tunnelling and Underground Space Technology, Journal Year: 2024, Volume and Issue: 154, P. 106081 - 106081

Published: Sept. 19, 2024

Language: Английский

Citations

5
Ground Settlement Prediction in Urban Tunnelling: Leveraging Metaheuristic-Optimized Random Forest Models DOI Creative Commons
Peixi Yang, Jian Zhou, Yulin Zhang

et al.

Arabian Journal for Science and Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: March 5, 2025

Abstract With the continuous acceleration of urbanization, problem ground settlement induced by underground tunnel construction has received more and widespread attention. This study addresses challenge predicting surface subsidence in urban construction, a critical concern geotechnical engineering. Random forest (RF) models were optimized using three distinct metaheuristic algorithms: ant lion optimizer (ALO), multiverse (MVO), grasshopper optimization algorithm (GOA). The enhancements significantly improved model accuracy, as demonstrated detailed performance metrics GOA-optimized RF (GOA-RF Pop = 20) on Changsha Metro Line 3 dataset, which included 294 instances 12 feature parameters. achieved an MAE 1.3820, MAPE 181.2249, correlation coefficient 0.9273, RMSE 2.5209 training set; 2.4695, 275.2054, R value 0.8877, 4.2540 testing set. A sensitivity analysis within random framework revealed that torque (To) condition (Gc) had most significant impact subsidence, whereas influence modified dynamic penetration test (MDPT) was least pronounced. Additionally, MATLAB-based application developed App Designer module, integrating these into user-friendly GUI facilitates prediction management risks, thereby enhancing practical effectiveness engineering risk mitigation strategies.

Language: Английский

Citations

0
Surrounding rock grade identification of deep TBM tunnel based on data decomposition and model fusion DOI
Kang Fu,

Daohong Qiu,

Yiguo Xue

et al.

Tunnelling and Underground Space Technology, Journal Year: 2025, Volume and Issue: 163, P. 106760 - 106760

Published: May 26, 2025

Language: Английский

Citations

0
Artificial intelligence driven tunneling-induced surface settlement prediction DOI
Ming Song,

Minghui Yang,

Guiqing Yao

et al.

Automation in Construction, Journal Year: 2024, Volume and Issue: 168, P. 105819 - 105819

Published: Oct. 17, 2024

Language: Английский

Citations

3
Enhancing Mine Blasting Safety: Developing Intelligent Systems for Accurate Flyrock Prediction through Optimized Group Method of Data Handling Methods DOI
Xiaohua Ding, Mahdi Hasanipanah, Masoud Monjezi

et al.

Natural Resources Research, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 21, 2024

Language: Английский

Citations

1