In EDS ansehen

Situation Model of the Transport, Transport Emissions and Meteorological Conditions

Gespeichert in:
Bibliographische Detailangaben
Titel: Situation Model of the Transport, Transport Emissions and Meteorological Conditions
Autoren: Beneš, Viktor, Svítek, Miroslav, Michalíková, Alžbeta, Melicherčík, Miroslav
Quelle: Neural Network World. 34:27-36
Publication Status: Preprint
Verlagsinformationen: Czech Technical University in Prague - Central Library, 2024.
Publikationsjahr: 2024
Schlagwörter: transportation, inteligentné mestá, FOS: Computer and information sciences, smart cities, cestná premávka, Takagi-Sugeno fuzzy interferenčné systémy, emissions, road traffic, 02 engineering and technology, Machine Learning (cs.LG), Machine Learning, Artificial Intelligence (cs.AI), Artificial Intelligence, 13. Climate action, emisie, transport, 11. Sustainability, 0202 electrical engineering, electronic engineering, information engineering, dopravné služby, doprava
Beschreibung: 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.
Publikationsart: Article
Dateibeschreibung: application/pdf
ISSN: 2336-4335
DOI: 10.14311/nnw.2024.34.002
DOI: 10.48550/arxiv.2509.10541
Zugangs-URL: http://arxiv.org/abs/2509.10541
Rights: CC BY
Dokumentencode: edsair.doi.dedup.....f170b4d3ded97b0ceaef0f7f2a076de7
Datenbank: OpenAIRE
Beschreibung
Abstract: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.
ISSN:23364335
DOI:10.14311/nnw.2024.34.002