Rockburst prediction and classification based on the ideal-point method of information theory

doi:10.1016/j.tust.2018.07.014

CORC > 地质与地球物理研究所 > 中国科学院地质与地球物理研究所 > 中国科学院页岩气与地质工程重点实验室

	Rockburst prediction and classification based on the ideal-point method of information theory
	Xu, Chen 1; Liu, Xiaoli 1; Wang, Enzhi 1; Zheng, Yanlong 2; Wang, Sijing 3
刊名	TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
	2018-11-01
卷号	81 页码:382-390
关键词	Rockburst prediction Ideal point method Information theory Principal component analysis Mutual information entropy
ISSN号	0886-7798
DOI	10.1016/j.tust.2018.07.014
英文摘要	A rockburst is a sudden dynamic process under high geostress conditions where rocks spontaneously explode. This is an important geological problem for underground construction processes. A rockburst could lead to equipment damage, casualties, and construction delays. Therefore, rockburst prediction and classification are extremely significant. A prediction and classification model is established by introducing the basic theory of the ideal-point method, considering the rockburst mechanism. Three parameters are selected as evaluation indexes, including the rock stress coefficient (sigma(theta)/sigma(c)), rock brittleness coefficient (sigma(c)/sigma(t)), and elastic energy index (M-et). To eliminate any correlation between the parameters, a principal component analysis based on mutual information (MIPCA) for the rockburst feature selection is used to calculate a new group of parameters. Then, using the information-entropy theory, the weight coefficients of these new evaluation indexes are confirmed. Finally, using statistics-related projects, engineering-case analyses show the feasibility and applicability of the proposed model. A computer evaluation program with a rockburst-classification interface was developed, based on the proposed model. This model and computer software can be used for other similar engineering practices in the future.
资助项目	National Key Research and Development Plan[2016YFC0501104] ; National Natural Science Foundation Outstanding Youth Foundation[51522903] ; National Natural Science Foundation of China[51479094]
WOS关键词	SELECTION ; SUPPORT ; HAZARD
WOS研究方向	Construction & Building Technology ; Engineering
语种	英语
出版者	PERGAMON-ELSEVIER SCIENCE LTD
WOS记录号	WOS:000446949500033
资助机构	National Key Research and Development Plan ; National Key Research and Development Plan ; National Natural Science Foundation Outstanding Youth Foundation ; National Natural Science Foundation Outstanding Youth Foundation ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Key Research and Development Plan ; National Key Research and Development Plan ; National Natural Science Foundation Outstanding Youth Foundation ; National Natural Science Foundation Outstanding Youth Foundation ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Key Research and Development Plan ; National Key Research and Development Plan ; National Natural Science Foundation Outstanding Youth Foundation ; National Natural Science Foundation Outstanding Youth Foundation ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Key Research and Development Plan ; National Key Research and Development Plan ; National Natural Science Foundation Outstanding Youth Foundation ; National Natural Science Foundation Outstanding Youth Foundation ; National Natural Science Foundation of China ; National Natural Science Foundation of China
内容类型	期刊论文
源URL	[http://ir.iggcas.ac.cn/handle/132A11/89180]
专题	地质与地球物理研究所_中国科学院页岩气与地质工程重点实验室
通讯作者	Liu, Xiaoli
作者单位	1.Tsinghua Univ, State Key Lab Hydro Sci & Engn, Beijing 100084, Peoples R China 2.Monash Univ, Dept Civil Engn, Clayton, Vic 3800, Australia 3.Chinese Acad Sci, Inst Geol & Geophys, Beijing 100029, Peoples R China
推荐引用方式 GB/T 7714	Xu, Chen,Liu, Xiaoli,Wang, Enzhi,et al. Rockburst prediction and classification based on the ideal-point method of information theory[J]. TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY,2018,81:382-390.
APA	Xu, Chen,Liu, Xiaoli,Wang, Enzhi,Zheng, Yanlong,&Wang, Sijing.(2018).Rockburst prediction and classification based on the ideal-point method of information theory.TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY,81,382-390.
MLA	Xu, Chen,et al."Rockburst prediction and classification based on the ideal-point method of information theory".TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY 81(2018):382-390.