A review of tunnel rockburst prediction methods based on static and dynamic indicators-Reference-Cited by-同舟云学术

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A review of tunnel rockburst prediction methods based on static and dynamic indicators

Published:2024-05-18 Issue: Volume: Page:
ISSN:0921-030X
Container-title:Natural Hazards
language:en
Short-container-title:Nat Hazards

Author:

Zhang Qinghe,Li Weiguo,Yuan Liang,Zheng Tianle,Liang Zhiwei,Wang Xiaorui

Funder

the National Engineering Research Centre Open Project

the National Major Research Instrument Development Project

the Anhui Provincial Universities Outstanding Young Research Funding Project

the Anhui Provincial Universities Collaborative Innovation Funding Project

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11069-024-06657-3.pdf

Reference195 articles.

1. Adoko AC, Gokceoglu C, Wu L, Zuo QJ (2013) Knowledge-based and data-driven fuzzy modeling for rockburst prediction. Int J Rock Mech Min Sci 61:86–95. https://doi.org/10.1016/j.ijrmms.2013.02.010

2. Afraei S, Shahriar K, Madani SH (2019) Developing intelligent classification models for rock burst prediction after recognizing significant predictor variables, section: Literature review and data preprocessing procedure. Tunn Undergr Space Technol 83:324–353

3. Ban YX, Fu X, Xie Q (2020) Revealing the laminar shale microdamage mechanism considering the relationship between fracture geometrical morphology and acoustic emission power spectrum characteristics. Bull Eng Geol Environ 79(2):1083–1096. https://doi.org/10.1007/s10064-019-01599-8

4. Barton N, Lien R, Lunde J (1974) Engineering classification of rock masses for the design of tunnel support. Rock Mech 6:189–236

5. Becker D, Cailleau B, Dahm T, Shapiro S, Kaiser D (2010) Stress triggering and stress memory observed from acoustic emission records in a salt mine. Geophys J Int 182(2):933–948. https://doi.org/10.1111/j.1365-246X.2010.04642.x

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1. Applying machine learning approach in predicting short-term rockburst risks using microseismic information: a comparison of parametric and non-parametric models;Natural Hazards;2024-08-06

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