Rockburst prediction and classification based on the ideal-point method of information theory-Reference-Cited by-同舟云学术

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

Published:2018-11 Issue: Volume:81 Page:382-390
ISSN:0886-7798
Container-title:Tunnelling and Underground Space Technology
language:en
Short-container-title:Tunnelling and Underground Space Technology

Author:

Xu Chen^ORCID,Liu Xiaoli^ORCID,Wang Enzhi,Zheng Yanlong^ORCID,Wang Sijing

Funder

National Key Research and Development Plan

National Natural Science Foundation-Outstanding Youth Foundation

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Geotechnical Engineering and Engineering Geology,Building and Construction

Reference52 articles.

1. Study on a neutral network model and its application in predicting the risk of rock blast;Bai;China Saf. Sci. J.,2002

2. Using mutual information for selecting features in supervised neural net learning;Battiti;Ieee. T. Neural. Networ,1994

3. Principles of rock support in burst-prone ground;Cai;Tunn. Undergr. Sp. Technol,2013

4. Prediction and prevention of rockburst in metal mines – a case studyof Sanshandao gold mine;Cai;J. Rock Mech. Geotech. Eng.,2016

5. Detecting communities in social networks using label propagation with information entropy;Chen;Phys. A (Amsterdam, Neth.),2016

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