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
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Title
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
Authors
Keywords
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Journal
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
Volume 122, Issue -, Pages 106107
Publisher
Elsevier BV
Online
2023-03-17
DOI
10.1016/j.engappai.2023.106107
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