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Annals of Computer Science and Information Systems, Volume 23

Communication Papers of the 2020 Federated Conference on Computer Science and Information Systems

Sensitivity Study of a Large-Scale Air Pollution Model by Using Optimized Stochastic Algorithm

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DOI: http://dx.doi.org/10.15439/2020F107

Citation: Communication Papers of the 2020 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 23, pages 2932 ()

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Abstract. In this work a systematic procedure for multidimensional sensitivity analysis in the area of air pollution modeling by an optimized latin hypercube sampling has been done. The Unified Danish Eulerian Model (UNI-DEM) is used in our work, because this model is one of the most advanced large-scale mathematical models that describes adequately all physical and chemical processes. We study with new optimized stochastic method the sensitivity of concentration variations of some of the most dangerous air pollutants with respect to the anthropogenic emissions levels and with respect to some chemical reactions rates.


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