Bayesian comparison of stochastic models of dispersion

Bayesian comparison of stochastic models of dispersion

Stochastic models of varying complexity have been proposed to describe the dispersion of particles in turbulent flows, from simple Brownian motion to complex temporally and spatially correlated models. A method is needed to compare competing models, accounting for the difficulty in estimating the ad...

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Bibliographic Details
Main Authors: Brolly, M.T (Author), Maddison, J.R (Author), Teckentrup, A.L (Author), Vanneste, J. (Author)
Format: Article
Language:English
Published: Cambridge University Press 2022
Subjects:
Bayesian
Bayesian networks
Brownian movement
Competing models
Complex model
Correlated model
Data-driven methods
dispersion
Dispersions
machine learning
Machine learning
Machine-learning
Simple++
Stochastic models
Stochastic systems
Stochastic-modeling
Time-scales
Turbulent flow
turbulent mixing
Turbulent mixing
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