Application of Bayesian networks for accuracy estimation of modeling results of the air pollution dispersion given inaccurate input data

Authors

  • Regina V. Kryvakovska “Mama Products” Ltd, Kyiv, Ukraine

DOI:

https://doi.org/10.20535/SRIT.2308-8893.2020.2.06

Keywords:

atmospheric air assessment, Bayesian networks

Abstract

The article deals with estimating the results accuracy of the modeling of air pollution dispersion when introducing inaccurate input data. Restrictions on accuracy estimation methods for Ukraine are considered. It is suggested to use Bayesian networks with discrete input variables to obtain the estimates. The structure of the network is presented, and the methods of filling the probability tables are proposed.

Author Biography

Regina V. Kryvakovska, “Mama Products” Ltd, Kyiv

Regina Kryvakovska,

a programmer at “Mama Products” Ltd, Kyiv, Ukraine.

References

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D. Heckerman, “A Tutorial on Learning with Bayesian Networks”, Technical Report MSR-TR-95-06, Microsoft Research, 1995.

Published

2020-09-25

Issue

Section

Decision making and control in economic, technical, ecological and social systems