Results 11 to 20 of about 412 (171)

Analysis of key geological structures and rockburst prediction method [PDF]

Scientific Reports
Rockburst disasters generally occur within specific geological structures. Consequently, predicting and evaluating the potential rockbursts necessitates more focuses on the “geological carrier”. Considering the geological structure effects of rockbursts,
Chunchi Ma, Yang Yuan, Xiang Ji, Feng Peng, Ziquan Chen, Hang Zhang   +5 more
doaj   +4 more sources

Rockburst prediction and prevention in underground space excavation

Underground Space
The technical challenges associated with deep underground space activities have become increasingly significant. Among these challenges, one major concern is the assessment of rockburst risks and the instability of rock masses.
Jian Zhou, Yulin Zhang, Chuanqi Li, Haini He, Xibing Li   +4 more
doaj   +4 more sources

Ensemble stacking rockburst prediction model based on Yeo–Johnson, K-means SMOTE, and optimal rockburst feature dimension determination [PDF]

Scientific Reports, 2022
Rockburst forecasting plays a crucial role in prevention and control of rockburst disaster. To improve the accuracy of rockburst prediction at the data structure and algorithm levels, the Yeo–Johnson transform, K-means SMOTE oversampling, and optimal ...
Lijun Sun, Nanyan Hu, Yicheng Ye, Wenkan Tan, Menglong Wu, Xianhua Wang, Zhaoyun Huang   +6 more
doaj   +2 more sources

Rockburst Intensity Level Prediction Method Based on FA-SSA-PNN Model

Energies, 2022
To accurately and reliably predict the occurrence of rockburst disasters, a rockburst intensity level prediction model based on FA-SSA-PNN is proposed. Crding to the internal and external factors of rockburst occurrence, six rockburst influencing factors
Gang Xu, Kegang Li, Mingliang Li, Qingci Qin, Rui Yue   +4 more
doaj   +3 more sources

Combined prediction of rockburst based on multiple factors and stacking ensemble algorithm

Underground Space, 2023
Rockburst is a kind of common geological disaster in deep tunnel engineering. It has the characteristics of causing great harm and occurring at random locations and times.
Hu Luo, Yong Fang, Jianfeng Wang, Yubo Wang, Hang Liao, Tao Yu, Zhigang Yao   +6 more
doaj   +3 more sources

A self-supervision rockburst risk prediction algorithm based on automatic mining of rockburst prediction index features

Frontiers in Earth Science
The rockburst risk prediction based on microseismic (MS) data is an important research task in deep mine safety prevention. However, the lack of systematic research on explicit prediction indexes and the waste of a large amount of unlabeled data are ...
Xiufeng Zhang, Haikuan Zhang, Haitao Li, Guoying Li, Shanshan Xue, Haichen Yin, Yang Chen, Fei Han   +7 more
doaj   +2 more sources

Machine learning methods for rockburst prediction-state-of-the-art review

International Journal of Mining Science and Technology, 2019
One of the most serious mining disasters in underground mines is rockburst phenomena. They can lead to injuries and even fatalities as well as damage to underground openings and mining equipment.
Yuanyuan Pu, Derek B. Apel, Victor Liu, Hani Mitri   +3 more
doaj   +3 more sources

Prediction and Evaluation of Rockburst Based on Depth Neural Network

Advances in Civil Engineering, 2021
The formation mechanism of rockburst is complex, and its prediction has always been a difficult problem in engineering. According to the tunnel engineering data, a three-dimensional discrete element numerical model is established to analyze the initial ...
Jin Zhang, Mengxue Wang, Chuanhao Xi
doaj   +2 more sources

Rockburst prediction using artificial intelligence techniques: A review

Rock Mechanics Bulletin
Rockburst is a phenomenon where sudden, catastrophic failure of the rock mass occurs in underground deep regions or areas with high tectonic stress during the excavation process.
Yu Zhang, Kongyi Fang, Manchao He, Dongqiao Liu, Junchao Wang, Zhengjia Guo   +5 more
doaj   +3 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   +3 more sources