Prediction of Peak Shear Strength of Rock Joints Based on Back-Propagation Neural Network-Reference-Cited by-同舟云学术

Prediction of Peak Shear Strength of Rock Joints Based on Back-Propagation Neural Network

Published:2021-06 Issue:6 Volume:21 Page:04021085
ISSN:1532-3641
Container-title:International Journal of Geomechanics
language:en
Short-container-title:Int. J. Geomech.

Author:

Huang Man¹,Hong Chenjie²,Chen Jie²,Ma Chengrong³,Li Changhong⁴,Huang Yongliang⁵

Affiliation:

1. Associate Professor, Dept. of Civil Engineering, Shaoxing Univ., 508 Huancheng West Rd., Shaoxing 312000, China.

2. M.Sc. Candidate, Dept. of Civil Engineering, Shaoxing Univ., 508 Huancheng West Rd., Shaoxing 312000, China.

3. Associate Professor, Dept. of Civil Engineering, Shaoxing Univ., 508 Huancheng West Rd., Shaoxing 312000, China (corresponding author).

4. Professorate Senior Engineer, Zhejiang Bureau of Nonferrous Metal Geological Exploration, 160 Renmin Zhong Lu, Yuecheng District, Shaoxing 312000, China.

5. Senior Engineer, Zhejiang Bureau of Nonferrous Metal Geological Exploration, 160 Renmin Zhong Lu, Yuecheng District, Shaoxing 312000, China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Soil Science

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29GM.1943-5622.0002033

Reference33 articles.

1. Modeling deformation modulus of a stratified sedimentary rock mass using neural network, fuzzy inference and genetic programming;Alemdag S.;Eng. Geol.,2016

2. The shear strength of rock joints in theory and practice

3. An Experimental and Numerical Study on Mechanical Behavior of Ubiquitous-Joint Brittle Rock-Like Specimens Under Uniaxial Compression

4. Neural network prediction of the reliability of heterogeneous cohesive slopes

5. Approximation by superpositions of a sigmoidal function

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