Situation Model of the Transport, Transport Emissions and Meteorological Conditions
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21260%2F24%3A00377244" target="_blank" >RIV/68407700:21260/24:00377244 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21730/24:00377244
Result on the web
<a href="https://doi.org/10.14311/NNW.2024.34.002" target="_blank" >https://doi.org/10.14311/NNW.2024.34.002</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.14311/NNW.2024.34.002" target="_blank" >10.14311/NNW.2024.34.002</a>
Alternative languages
Result language
angličtina
Original language name
Situation Model of the Transport, Transport Emissions and Meteorological Conditions
Original language description
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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10500 - Earth and related environmental sciences
Result continuities
Project
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Continuities
V - Vyzkumna aktivita podporovana z jinych verejnych zdroju
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Neural Network World
ISSN
1210-0552
e-ISSN
2336-4335
Volume of the periodical
34
Issue of the periodical within the volume
1
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
10
Pages from-to
27-36
UT code for WoS article
001223719400001
EID of the result in the Scopus database
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