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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

Optimized Quasi-Monte Carlo Method Based on Low Discrepancy Sequences for Sensitivity Analysis in Air Pollution Modelling

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DOI: http://dx.doi.org/10.15439/2020F108

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 2528 ()

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Abstract. An optimization version of the van der Corput sequence has been used in our sensitivity studies of the model output results for some air pollutants with respect to the emission levels and some chemical reactions rates. Sensitivity analysis of model outputs to variation or natural uncertainties of model inputs is very significant for improving the reliability of these models. Clearly, the progress in the area of air pollution modeling,is closely connected with the progress in reliable algorithms for multidimensional integration.


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