Study on Thermal Conductivity Prediction of Granites Using Data Augmentation and Machine Learning

Study on Thermal Conductivity Prediction of Granites Using Data Augmentation and Machine Learning

With the global low-carbon energy transition, accurate prediction of thermal and physical parameters of deep rock masses is critical for geothermal resource development. To address the insufficient generalization ability of machine learning models caused by scarce measured data on granite thermal co...

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Bibliographic Details
Main Authors: Yongjie Ma, Lin Tian, Fuhang Hu, Jingyong Wang, Echuan Yan, Yanjun Zhang
Format: Article
Language:English
Published: MDPI AG 2025-08-01
Series:Energies
Subjects:
geothermal energy
thermal conductivity prediction
data augmentation
machine learning
Online Access:https://www.mdpi.com/1996-1073/18/15/4175
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