A prediction model on rockburst intensity grade based on variable weight and matter-element extension-Reference-Cited by-同舟云学术

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A prediction model on rockburst intensity grade based on variable weight and matter-element extension

Published:2019-06-26 Issue:6 Volume:14 Page:e0218525
ISSN:1932-6203
Container-title:PLOS ONE
language:en
Short-container-title:PLoS ONE

Author:

Chen Jianhong,Chen Yi,Yang Shan^ORCID,Zhong Xudong,Han Xu

Funder

National Natural Science Foundation Project of China

Graduated Students’ Research and Innovation Fund Project of Central South University.

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference54 articles.

1. Laboratory Experiments: Their Role in the Problem of Rock Burst Prediction;V A. Mansurov;Rock Testing & Site Characterization,1993

2. Knowledge-based and data-driven fuzzy modeling for rockburst prediction;A C Adoko;International Journal of Rock Mechanics & Mining Sciences,2013

3. Early assessment of dynamic rupture hazard for rockburst risk management in deep tunnel projects;M S. Diederichs;Journal of the Southern African Institute of Mining & Metallurgy,2018

4. Review on Rockburst Theory and Types of Rock Support in Rockburst Prone Mines;E Kabwe;Open Journal of Safety Science & Technology,2015

5. Intense rockburst impacts in deep underground construction and their prevention 1;A Mazaira;Canadian Geotechnical Journal,2015

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1. Research and Application of an Intelligent Prediction of Rock Bursts Based on a Bayes-Optimized Convolutional Neural Network;International Journal of Geomechanics;2023-05

2. Measurement and Classification Criteria of Strength Decrease Rate and Brittleness Indicator Index for Rockburst Proneness Evaluation of Hard Rocks;Materials;2023-04-14

3. A Novel Method for Predicting Rockburst Intensity Based on an Improved Unascertained Measurement and an Improved Game Theory;Mathematics;2023-04-14

4. A rockburst prediction model based on extreme learning machine with improved Harris Hawks optimization and its application;Tunnelling and Underground Space Technology;2023-04

5. Cooperative Efficiency Evaluation System for Intelligent Transportation Facilities Based on the Variable Weight Matter Element Extension;Sustainability;2023-01-29

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