Enhanced rock mass rating prediction from tunnel face imagery: A decision-supportive ensemble deep learning approach-Reference-Cited by-同舟云学术

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Enhanced rock mass rating prediction from tunnel face imagery: A decision-supportive ensemble deep learning approach

Published:2024-09 Issue: Volume:339 Page:107625
ISSN:0013-7952
Container-title:Engineering Geology
language:en
Short-container-title:Engineering Geology

Author:

Kim Yejin,Yun Tae Sup

Publisher

Elsevier BV

Reference35 articles.

1. A review and case study of Artificial intelligence and machine learning methods used for ground condition prediction ahead of tunnel boring Machines;Ayawah;Tunn. Undergr. Sp. Technol.,2022

2. Engineering classification of jointed rock masses;Bieniawski;Civ. Eng.,1973

3. Bagging predictors;Breiman;Mach. Learn.,1996

4. A new version of the generalized Zhang–Zhu strength criterion and a discussion on its smoothness and convexity;Cai;Rock Mech. Rock. Eng.,2021

5. Image-based segmentation and quantification of weak interlayers in rock tunnel face via deep learning;Chen;Autom. Constr.,2020

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