Sparse and hybrid modelling of relative humidity: the Krško basin case study

Sparse and hybrid modelling of relative humidity: the Krško basin case study

This study describes an application of hybrid modelling for an atmospheric variable in the Krško basin. The hybrid model is a combination of a physics-based and data-driven model and has some properties of both modelling approaches. In the authors’ case, it is used for the modelling of an atmospheri...

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Bibliographic Details
Main Authors: Juš Kocijan, Matija Perne, Boštjan Grašic, Marija Zlata Božnar, Primož Mlakar
Format: Article
Language:English
Published: Wiley 2019-12-01
Series:CAAI Transactions on Intelligence Technology
Subjects:
environmental science computing
air pollution
learning (artificial intelligence)
regression analysis
gaussian processes
humidity
geophysics computing
physics-based atmospherical model
gaussian-process regression model
gp model
sparse gp modelling
empirical model training
physics-based model
hybrid modelling
relative humidity
krško basin case study
atmospheric variable
data-driven model
air-pollution-dispersion model
Online Access:https://digital-library.theiet.org/content/journals/10.1049/trit.2019.0054

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