Results 101 to 110 of about 4,719,386 (185)

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

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

Performance Evaluation of Hybrid PSO-BPNN-AdaBoost and PSO-BPNN-XGBoost Models for Rockburst Prediction with Imbalanced Datasets

Applied Sciences
The rockburst hazard is a primary geological disaster endangering the environment in underground engineering. Due to the complexity of the rockburst mechanism, traditional methods are insufficient to predict the rockburst hazard objectively, especially ...
Shujian Li, Pengpeng Lu, Weizhang Liang, Ying Chen, Qi Da   +4 more
semanticscholar   +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

Research on Temporal and Spatial Distribution Characteristics of Microseismic Events of Slip-Type Rockburst

, 2022
Based on the microseismic monitoring data of underground cavern of Shuangjiangkou Hydropower Station, the internal relationship between rockburst and microseismic events is analyzed and the occurrence mechanism of slip-type rockburst in underground ...
Ge Yan, Kun Xu, Leibo Song, Wenjie Song, Gang Wang, Qin Chen, Jiangtao He, Liping Li   +7 more
core   +1 more source

AN INSIGHT OF ROCKBURST INTENSITY PREDICTION USING MACHINE LEARNING

, 2022
Rockburst is a violent explosion of rock, which happens mostly in high geo-stress conditions in underground excavations. This phenomenon occurs due to of the sudden release of strain energy stored in rock mass.
Kulgatov, Amir
core  

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

LSTM-based rockburst risk prediction model incorporating attention mechanism and convolutional neural networks and its applications

矿业科学学报
Rockburst is particularly hazardous, rendering the accurate prediction of rockburst risks one of the urgent challenges in this field of research. This study proposes and establishes a long short-term memory (LSTM) rockburst risk prediction model (CAL ...
ZHANG Yu, WANG Junchao, GUO Zhengjia, FANG Kongyi   +3 more
doaj   +1 more source

Prediction of Rockburst at Mufulira Mine, Copperbelt, Zambia

, 2023
The overall aim of this study is to provide methods for prediction of rockburst in deep underground mines, using Mufulira mine in Zambia's Copperbelt as a case study.
Sinkala, Pardon
core  

The Spatiotemporal Distribution Law of Microseismic Events and Rockburst Characteristics of the Deeply Buried Tunnel Group

, 2018
Rockburst disaster is one of the prominent problems faced by deep underground engineering. Microseismic (MS) monitoring techniques can be used to warn of rockburst in tunnels to provide scientific basis for rock burst prevention and control measures ...
Jianchun Sun, Jiasong Yang, Liang Chen, Heng Zhang, Shougen Chen   +4 more
core   +1 more source