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  2. 地质与地球物理研究所
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  4. 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

文献类型：期刊论文

作者Xu, Chen1; Liu, Xiaoli1; Wang, Enzhi1; Zheng, Yanlong2; Wang, Sijing3
刊名TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
出版日期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
DOI10.1016/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.
WOS关键词SELECTION ; SUPPORT ; HAZARD
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研究方向Construction & Building Technology ; Engineering
语种英语
WOS记录号WOS:000446949500033
出版者PERGAMON-ELSEVIER SCIENCE LTD
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
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.

入库方式： OAI收割

来源：地质与地球物理研究所

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