Application of Relationship model for the Measurement While Drilling Data to Predict Rock Uniaxial Compressive Strength for Tunneling-Reference-Cited by-同舟云学术

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Application of Relationship model for the Measurement While Drilling Data to Predict Rock Uniaxial Compressive Strength for Tunneling

Published:2024-05-03 Issue: Volume: Page:
ISSN:0723-2632
Container-title:Rock Mechanics and Rock Engineering
language:en
Short-container-title:Rock Mech Rock Eng

Author:

Zhao Ruijie,Shi Shaoshuai^ORCID,Yao Rubing,Yang Shijie

Funder

National Natural Science Foundation of China

Innovation Team of Shandong Provincial Higher Education Youth Innovation and Technology Program

Taishan Scholar Foundation of Shandong Province

Shandong University Future Scholars program

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s00603-024-03907-5.pdf

Reference34 articles.

1. Auerbach F (1891) Absolute hardness measurements. Ann Phys Chem 43:61–100

2. Ceryan N, Okkan U, Kesimal A (2013) Prediction of unconfined compressive strength of carbonate rocks using artificial neural networks. Environ Earth Sci 68(3):807–819. https://doi.org/10.1007/s12665-012-1783-z

3. Cevik A, Sezer EA, Cabalar AF, Gokceoglu C (2011) Modeling of the uniaxial compressive strength of some clay-bearing rocks using neural network. Appl Soft Comput 11(2):2587–2594. https://doi.org/10.1016/j.asoc.2010.10.008

4. Dadhich S, Sharma JK, Madhira M (2022) Prediction of uniaxial compressive strength of rock using machine learning. J Inst Eng (india) Ser A 103(4):1209–1224. https://doi.org/10.1007/s40030-022-00688-4

5. He M, Zhang Z, Ren J et al (2019) Deep convolutional neural network for fast determination of the rock strength parameters using drilling data. Int J Rock Mech Min 123:104084. https://doi.org/10.1016/j.ijrmms.2019.104084

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