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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.

Xiaohong DaiHamid Taheri AndaniAs'ad AlizadehAzher M. AbedGhassan Fadhil SmaisimHamad Karem HadrawiMaryam KarimiMahmoud ShamsborhanDavood Toghraie
Published in: Eng. Appl. Artif. Intell. (2023)
Keyphrases
  • gaussian process regression
  • covariance function
  • gaussian processes
  • gaussian process
  • non stationary
  • bayesian framework
  • model selection
  • error rate
  • machine learning algorithms
  • missing data