Results 81 to 90 of about 1,572 (209)

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

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

Occurrence mechanism and prevention technology of rockburst, coal bump and mine earthquake in deep mining [PDF]

Rockburst, coal bump, and mine earthquake are the most important dynamic disaster phenomena in deep mining. This paper summarizes the differences and connections between rockburst, coal bumps and mine earthquakes in terms of definition, mechanism ...
Bi, Ruiyang, Du, Kun, Khandelwal, Manoj, Li, Guichen, Zhou, Jian   +4 more
core   +2 more sources

An Improved SMOTE Algorithm Based on Genetic Algorithm for Imbalanced Data Collection [PDF]

, 2016
Classification of imbalanced data has been recognized as a crucial problem in machine learning and data mining. In an imbalanced dataset, minority class instances are likely to be misclassified. When the synthetic minority over-sampling technique (SMOTE)
Gu, Qiong, Ning, Bing, Wang, Xian-Ming, Wu, Zhao, Xin, Chun-Sheng   +4 more
core   +1 more source

Application of a new brittleness index to estimate the proneness to brittle failure of rock around a deep tunnel [PDF]

, 2023
A major problem that may arise during the excavation of deep tunnels is the incidence of brittle failure of rock, induced by the stress release in a particularly heavy natural state of stress.
Barbero, Monica, Borri-Brunetto, Mauro, Milan, Lorenzo   +2 more
core  

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

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

Comparative analysis and application of rockburst prediction model based on secretary bird optimization algorithm

Frontiers in Earth Science
The accurate rockburst prediction is crucial for ensuring the safety of underground engineering construction. Among the various methods, machine learning-based rockburst prediction can better solve the nonlinear relationship between rockbursts and ...
Tengjie Yang, Tengjie Yang, Xinqiang Gao, Xinqiang Gao, Lichuan Wang, Yongqing Xue, Haobo Fan, Zhengguo Zhu, Zhengguo Zhu, Jingbo Zhao, Beiyi Dong, Beiyi Dong   +11 more
doaj   +1 more source

Novel rockburst prediction criterion with enhanced explainability employing CatBoost and nature-inspired metaheuristic technique

Underground Space
Rockburst is a major challenge to hard rock engineering at great depth. Accurate and timely assessment of rockburst risk can avoid unnecessary casualties and property losses.
Yingui Qiu, Jian Zhou
doaj   +1 more source

A new method to assess the possibility of brittle failure of rock induced by deep excavations [PDF]

Spalling and rockburst are severe criticalities that can emerge while excavating deep tunnels in rock masses under heavy natural stress states. Here, rock brittle failure can induce massive releases of the energy stored during the excavation and ...
Barbero, Monica, Borri-Brunetto, Mauro, Milan, Lorenzo   +2 more
core   +1 more source