Results 11 to 20 of about 2,608,139 (189)

A review on rockburst prediction and prevention to shape an ontology‐based framework for better decision‐making for underground excavations

Deep Underground Science and Engineering, EarlyView.
With underground engineering projects becoming deeper and more complex, the associated safety problems, especially rockburst, have increasingly increased.
Hongchuan Yan, Haijiang Li, Hongqiang Xie, Mingli Xiao, Jian-liang Pei, Huaizhong Liu, Jiangda He   +6 more
semanticscholar   +2 more sources

Rockburst prediction based on data preprocessing and hyperband‐RNN‐DNN

Deep Underground Science and Engineering, EarlyView.
A data preprocessing workflow is proposed to address key challenges in rockburst data analysis, including dimensionality differences among various sample features, variations in data values within the same feature, missing data, poor data consistency ...
Yong Fan, Chenxi Yin, G. Yang, Shengyong Ding, Bin Tian   +4 more
semanticscholar   +2 more sources

Rockburst prediction based on optimization of unascertained measure theory with normal cloud

Complex & Intelligent Systems, 2023
Rockburst is one of the common geological disasters in deep underground areas with high stress. Rockburst prediction is an important measure to know in advance the risk of rockburst hazards to take a scientific approach to the response.
Xingmiao Hu, Linqi Huang, Jiangzhan Chen, Xibing Li, Hongzhong Zhang   +4 more
doaj   +2 more sources

Novel Ensemble Tree Solution for Rockburst Prediction Using Deep Forest

Mathematics, 2022
The occurrence of rockburst can cause significant disasters in underground rock engineering. It is crucial to predict and prevent rockburst in deep tunnels and mines. In this paper, the deficiencies of ensemble learning algorithms in rockburst prediction
Diyuan Li, Zida Liu, Danial Jahed Armaghani, Peng Xiao, Jian Zhou   +4 more
doaj   +2 more sources

Rockburst prediction based on multi-featured drilling parameters and extreme tree algorithm for full-section excavated tunnel faces

Journal of Rock Mechanics and Geotechnical Engineering
The suddenness, uncertainty, and randomness of rockbursts directly affect the safety of tunnel construction. The prediction of rockbursts is a fundamental aspect of mitigating or even eliminating rockburst hazards.
Wenhao Yi, Mingnian Wang, Qinyong Xia, Yongyi He, Hongqiang Sun   +4 more
doaj   +2 more sources

Intelligent rockburst prediction model with sample category balance using feedforward neural network and Bayesian optimization

Underground Space, 2022
The rockburst prediction becomes more and more challenging due to the development of deep underground projects and constructions. Increasing numbers of intelligent algorithms are used to predict and prevent rockburst.
Diyuan Li, Zida Liu, Peng Xiao, Jian Zhou, Danial Jahed Armaghani   +4 more
doaj   +2 more sources

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   +2 more sources

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   +2 more sources

A prototype-based rockburst types and risk prediction algorithm considering intra-class variance and inter-class distance of microseismic data

Frontiers in Earth Science
The prediction and classification of rockburst risk based on microseismic data is the premise of preventing rockbursts during deep mine excavation. By reviewing previous studies, this paper finds two problems that hinder the rockburst prediction: 1 ...
Xiufeng Zhang, Guoying Li, Yang Chen, Hao Wang, Haikuan Zhang, Haitao Li, Weisheng Du, Xiao Li, Xuewei Xu, Yuze He   +9 more
doaj   +2 more sources

Distriformer: Research on a Distributed Training Rockburst Prediction Method

Processes
The precise forecasting of rockburst is fundamental for safeguarding human lives and property, upholding national energy security, and protecting social welfare. Traditional methods for predicting rockburst suffer from poor accuracy and extended model training durations.
Yu Zhang, Kongyi Fang, Zhengjia Guo
openaire   +2 more sources