Uncertainty quantification based on symbolic regression and probabilistic programming and its application

Uncertainty quantification based on symbolic regression and probabilistic programming and its application

The joint roughness coefficient (JRC) is critical to evaluate the strength and deformation behavior of joint rock mass in rock engineering. Various methods have been developed to estimate JRC value based on the statistical parameter of rock joints. The JRC value is uncertain due to the complex, rand...

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Bibliographic Details
Main Authors: Yuyang Zhao, Hongbo Zhao
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:Machine Learning with Applications
Subjects:
Rock joint
Joint roughness coefficient
Uncertainty quantification
Symbolic regression
Probabilistic programming
Online Access:http://www.sciencedirect.com/science/article/pii/S2666827025000155

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http://www.sciencedirect.com/science/article/pii/S2666827025000155

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