Beneš, ViktorSvítek, MiroslavMichalíková, AlžbetaMelicherčík, Miroslav2025-09-192025-09-1920241210-05522336-4335https://doi.org/10.14311/NNW.2024.34.002https://repo.umb.sk/handle/123456789/829In: Neural Network World : international journal on non-standard computing and artificial intelligence. Praha : Czech Technical University in Prague, 2024. ISSN 1210-0552. Vol. 34, no. 1 (2024), pp. 27-36.Air pollution in cities and the possibilities of reducing this pollution represent one of the most important factors that today’s society has to deal with. This paper focuses on a systemic approach to traffic emissions with their relation to meteorological conditions, analyzing the effect of weather on the quantity and dispersion of traffic emissions in a city. Using fuzzy inference systems (FIS) the model for predicting changes in emissions depending on various conditions is developed. The proposed model is based on traffic, meteorology and emission data measured in Prague, Czech Republic. The main objective of the work is to provide insight into how urban planners and policymakers can plan and manage urban transportation more efficiently with environmental protection in mind.eninfo:eu-repo/semantics/openAccessdopravatransportationtransportemisieemissionsdopravné službyinteligentné mestásmart citiescestná premávkaroad trafficTakagi-Sugeno fuzzy interferenčné systémyArticle