Results 41 to 50 of about 2,276 (212)
, 2020 Rockburst dataset based on the indicators from the microseismic monitoring system in tunnels. There are four rockburst risk levels: none (34 cases), slight (21 cases), moderate (25 cases) and intense (11 cases).
Liang, W (via Mendeley Data)
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Novel Ensemble Tree Solution for Rockburst Prediction Using Deep Forest
, 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 +4 more
core +1 more source
Digital rock mechanics solutions for underground engineering problems such as coal mining
Meitan kexue jishuThe observability of underground engineering, such as coal mining, is extremely limited, which makes it difficult to obtain reliable pre-analysis basis for many complex engineering problems. Especially in face of new engineering environment brought about
Haitao LI +12 more
doaj +1 more source
A Decision Tree for Rockburst Conditions Prediction
Applied Sciences, 2023 This paper presents an alternative approach to predict rockburst using Machine Learning (ML) algorithms. The study used the Decision Tree (DT) algorithm and implemented two approaches: (1) using DT model for each rock type (DT-RT), and (2) developing a single DT model (Unique-DT) for all rock types.
Dominic Owusu-Ansah +4 more
openaire +3 more sources
Development and application of a rockburst database management system
工程科学学报, 2022 Aiming at the research problems on rockbursts in the forefront of deep rock mass engineering science, the challenges restricting its quantitative dynamics and intelligent warning research were analyzed.
Zhi-bin YAO +4 more
doaj +1 more source
Construction of a Two-Stage Rockburst Warning Model Based on Multi-Source Rockburst Case Studies
IEEE Access, 2023 Rock burst is a sudden disaster that is influenced by various factors. Accurately identifying and predicting rock burst risks is of great significance for improving mine safety. In order to improve the accuracy of rock burst prediction from the perspective of data structure, this paper constructs a two-level prediction model based on six rock burst ...
Jin Shang +3 more
openaire +2 more sources
Deep Underground Science and Engineering, EarlyView.This study examines energy evolution in rock rupture via triaxial direct shear tests, exploring the impact of confining pressure and temperature on fracture surface randomness. A novel energy‐based brittleness index is proposed, validated experimentally, and compared with existing methods for reliability and accuracy.
Biao Wang +5 more
wiley +1 more source
Study on the Mechanism of Rockburst Induced by Tidal Force
, 2021 According to the statistical analysis of the time and region of rockburst, it is found that the time and region of rockburst have a certain correlation with the change of tidal force.
Gaochuan GUO, Yongkang YANG
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工程科学学报Various defect structures exist in coal and rock masses, including cracks and pores, which significantly affect the occurrence and migration of coalbed methane.
Ziyue JIN +4 more
doaj +1 more source
Deep Underground Science and Engineering, EarlyView.In response to the problem of strong mining pressure manifestation along the goaf roadway in a thick coal seam mining area, this study uses a new type of combined blasting roof cutting technology to effectively control the manifestation and deformation of mining pressure along the goaf roadway.
Xiaoding Xu +6 more
wiley +1 more source