Developing intelligent classification models for rock burst prediction after recognizing significant predictor variables, Section 1: Literature review and data preprocessing procedure-Reference-Cited by-同舟云学术

Developing intelligent classification models for rock burst prediction after recognizing significant predictor variables, Section 1: Literature review and data preprocessing procedure

Published:2019-01 Issue: Volume:83 Page:324-353
ISSN:0886-7798
Container-title:Tunnelling and Underground Space Technology
language:en
Short-container-title:Tunnelling and Underground Space Technology

Author:

Afraei Sajjad,Shahriar Kourosh,Madani Sayyed Hassan

Publisher

Elsevier BV

Subject

Geotechnical Engineering and Engineering Geology,Building and Construction

Reference172 articles.

1. Knowledge-based and data-driven fuzzy modeling for rockburst prediction;Adoko;Int. J. Rock Mech. Min. Sci.,2013

2. Aydan, O. et al., 2001. Assessment of susceptibility of rock bursting in tunnelling in hard rocks. In: Adachi, et al. (Eds.), Proceeding of the Conference on Modern Tunnelling Science and Technology, Kyoto, Japan.

3. The squeezing potential of rocks around tunnels; theory and prediction;Aydan;Rock Mech. Rock Eng.,1993

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

5. Finite element analysis of rockburst as surface instability;Bardet;Comput. Geotech.,1989

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