Using Gaussian Process Regression (GPR) models with the Matérn covariance function to predict the dynamic viscosity and torque of SiO2/Ethylene glycol nanofluid: A machine learning approach

标题
Using Gaussian Process Regression (GPR) models with the Matérn covariance function to predict the dynamic viscosity and torque of SiO2/Ethylene glycol nanofluid: A machine learning approach
作者
关键词
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出版物
出版商
Elsevier BV
发表日期
2023-03-17
DOI
10.1016/j.engappai.2023.106107

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