Results 61 to 70 of about 422 (172)

LSTM multivariate model based microseismic time-series prediction and rockburst early warning

Frontiers in Earth Science
Aiming at the prominent rockburst risk in deep mining of Kongzhuang coal mine with high in-situ stress and thick hard roof, this study takes microseismic monitoring time-series data as the research object, and constructs a set of rockburst prediction and
Zenglun Guan, Feng Jin, Hui Zhao, Peng Wang, Yubao Zhao, Yubao Zhao, Lingjin Zhu, Qiang Yuan, Yulong Chen   +8 more
doaj   +1 more source

Dynamic Probabilistic Prediction of Rockburst Using a Dual‐Modality Model With Multisource Monitoring Data

Advances in Civil Engineering, Volume 2026, Issue 1, 2026.
Rockburst, due to its suddenness, randomness, and harmfulness, is one of the main factors restricting the safe construction of deep underground engineering. To achieve accurate prediction of rockburst occurrence probability, a dataset for drilling and blasting (D&B) tunnel construction was established using microseismic (MS) and geological data ...
Yong Xia, Xiya Li, Xin Li, Yifan He, Huabo Xiao, Longxiang Zhao, Yi Deng, Camelia Delcea   +7 more
wiley   +1 more source

Research Progress and Typical Cases of Deep Mines Backfill Technology in China

International Journal of Energy Research, Volume 2026, Issue 1, 2026.
With the increasing depletion of shallow mineral resources and the growing demand for metals, deep mining has become a strategic focus for China. However, deep mining operations face a series of complex challenges, including high ground stress, elevated geothermal gradients, and severe rockburst hazards.
Shuai Li, Zhenyu Dan, Haoxuan Yu, Zhenzhong Xiang, Junyu Chen, Luyu Wang   +5 more
wiley   +1 more source

Research on Prediction System for Rockburst Based on Artificial Intelligence Application Methods

工程科学与技术, 2010
:Based on theoretical analysis and on-the-spot monitoring methods, a prediction system for rockburst consisting of long-term and short-term predicting models was proposed.
Peng Qi, Qian Aiguo, Xiao Yu
doaj  

Predicting Model of Rockburst Based on Nondeterministic Theory [PDF]

, 2017
Predicting is the basis of prevention and controlling of rockburst hazards. Duo to the characteristic of sudden, disruptive, and complex, the accurate prediction of rockbursts is difficult and an urgent problem need to be solved. Rockburst tendency is an important metric to quantify the risk and potential intensity of occurrences and grade the hazard ...
openaire   +1 more source

Supervised and unsupervised general framework for rockburst risk prediction based on feature contrast of long-term and short-term microseismic data

Geomechanics and Geophysics for Geo-Energy and Geo-Resources
Short-term rockburst risk prediction based on microseismic (MS) data is a significant research task to overcome the rockburst challenge during the excavation stage. By reviewing previous short-term rockburst risk prediction methods based on MS data, this
Haikuan Zhang, Haitao Li, Xiufeng Zhang, Shanshan Xue, Haichen Ying, Atao Li, Jianwei Zheng, Xiaoshan Shi   +7 more
doaj   +1 more source

Recent advancements and emerging challenges in deep underground engineering

Deep Underground Science and Engineering, Volume 5, Issue 2, Page 313-314, June 2026.
Jianguo Wang, Chunfai Leung
wiley   +1 more source

Rockburst multi-factor coupling prediction and quantitative analysis of influencing Factors’ SHAP values based on TPE-FDM-XGBoost model

Ain Shams Engineering Journal
Accurately predicting rockburst and clarifying its influencing factors is a crucial support for ensuring the safe and efficient construction of underground projects, deepening the theory of geological disasters, and promoting engineering technology ...
Chao Peng, Wanrong Liu, Miao Liu, Xiao Wang, Xiaotong Du   +4 more
doaj   +1 more source

PNN-based Rockburst Prediction Model and Its Applications

Earth Sciences Research Journal, 2017
Rock burst is one of main engineering geological problems significantly threatening the safety of construction. Prediction of rock burst is always an important issue concerning the safety of workers and equipment in tunnels. In this paper, a novel PNN-based rock burst prediction model is proposed to determine whether rock burst will happen in the ...
Zhou, Yu, Wang, Tingling
openaire   +3 more sources

Interpretable model for rockburst intensity prediction based on Shapley values-based Optuna-random forest

Underground Space
To address the limitation of traditional machine learning models in explaining the rockburst intensity prediction process, this study proposes an interpretable rockburst intensity prediction model.
Yaxi Shen, Shunchuan Wu, Yongbing Wang, Jiaxin Wang, Zhiquan Yang   +4 more
doaj   +1 more source