A new integrated intelligent computing paradigm for predicting joints shear strength-Reference-Cited by-同舟云学术

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A new integrated intelligent computing paradigm for predicting joints shear strength

Published:2024-11 Issue:6 Volume:15 Page:101884
ISSN:1674-9871
Container-title:Geoscience Frontiers
language:en
Short-container-title:Geoscience Frontiers

Author:

Xie Shijie^ORCID,Jiang Zheyuan,Lin Hang,Ma Tianxing^ORCID,Peng Kang,Liu Hongwei,Liu Baohua

Publisher

Elsevier BV

Reference76 articles.

1. Machine-learning based landslide susceptibility modelling with emphasis on uncertainty analysis;Achu;Geosci Front,2023

2. Spatial landslide susceptibility assessment using machine learning techniques assisted by additional data created with generative adversarial networks;Al-Najjar;Geosci Front,2021

3. Constitutive modeling of rock fractures by improved support vector regression;Babanouri;Environ. Earth Sci.,2018

4. An ANFIS–TLBO criterion for shear failure of rock joints;Babanouri;Soft Comput.,2020

5. Experimental and numerical study of asperity degradation in the direct shear test;Bahaaddini;Eng. Geol.,2016

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1. Elastic modulus prediction for high-temperature treated rock using multi-step hybrid ensemble model combined with coronavirus herd immunity optimizer;Measurement;2025-01

2. Hybrid data-driven model for predicting the shear strength of discontinuous rock materials;Materials Today Communications;2024-12

3. Hybrid data-driven model and shapley additive explanations for peak dilation angle of rock discontinuities;Materials Today Communications;2024-08

4. Slope Stability Prediction Using Principal Component Analysis and Hybrid Machine Learning Approaches;Applied Sciences;2024-07-26

5. Hybrid machine learning models to predict the shear strength of discontinuities with different joint wall compressive strength;Nondestructive Testing and Evaluation;2024-07-22

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