GAM Modelling of Daily Number of Traffic Accidents as a Function of Meteorological Variables in the Czech Republic
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60162694%3AG42__%2F26%3A00564672" target="_blank" >RIV/60162694:G42__/26:00564672 - isvavai.cz</a>
Výsledek na webu
<a href="https://ejobsat.cz/artkey/ejo-202501-0007_gam-modelling-of-daily-number-of-traffic-accidents-as-a-function-of-meteorological-variables-in-the-czech-repub.php" target="_blank" >https://ejobsat.cz/artkey/ejo-202501-0007_gam-modelling-of-daily-number-of-traffic-accidents-as-a-function-of-meteorological-variables-in-the-czech-repub.php</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.11118/ejobsat.2024.014" target="_blank" >10.11118/ejobsat.2024.014</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
GAM Modelling of Daily Number of Traffic Accidents as a Function of Meteorological Variables in the Czech Republic
Popis výsledku v původním jazyce
Meteorological conditions exert a considerable influence on traffic patterns. This paper examines the influence of meteorological variables on the daily number of traffic accidents requiring fire brigade intervention. The influence of meteorological variables, including maximum temperature, wind speed, air pressure, precipitation, snow cover and sunshine, was examined. A Generalized Additive Model for variables with a Poisson distribution was employed for modelling purposes, as this allows for the representation of non-linear dependencies. The analysis demonstrates that the lowest incidence of accidents occurs at temperatures approximating 10 °C. The average daily number of accidents increases with windy weather, the minimum number of accidents occurs at zero precipitation, and the accident rate rises with higher levels of sunshine. In the Czech Republic, the period of greatest risk in terms of road traffic accidents is the summer and winter months. The findings may have several practical applications, for example, in the improvement of meteorological warnings in traffic.
Název v anglickém jazyce
GAM Modelling of Daily Number of Traffic Accidents as a Function of Meteorological Variables in the Czech Republic
Popis výsledku anglicky
Meteorological conditions exert a considerable influence on traffic patterns. This paper examines the influence of meteorological variables on the daily number of traffic accidents requiring fire brigade intervention. The influence of meteorological variables, including maximum temperature, wind speed, air pressure, precipitation, snow cover and sunshine, was examined. A Generalized Additive Model for variables with a Poisson distribution was employed for modelling purposes, as this allows for the representation of non-linear dependencies. The analysis demonstrates that the lowest incidence of accidents occurs at temperatures approximating 10 °C. The average daily number of accidents increases with windy weather, the minimum number of accidents occurs at zero precipitation, and the accident rate rises with higher levels of sunshine. In the Czech Republic, the period of greatest risk in terms of road traffic accidents is the summer and winter months. The findings may have several practical applications, for example, in the improvement of meteorological warnings in traffic.
Klasifikace
Druh
J<sub>SC</sub> - Článek v periodiku v databázi SCOPUS
CEP obor
—
OECD FORD obor
10103 - Statistics and probability
Návaznosti výsledku
Projekt
—
Návaznosti
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Ostatní
Rok uplatnění
2025
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
European Journal of Business Science and Technology
ISSN
2336-6494
e-ISSN
2694-7161
Svazek periodika
11
Číslo periodika v rámci svazku
1
Stát vydavatele periodika
CZ - Česká republika
Počet stran výsledku
16
Strana od-do
23-38
Kód UT WoS článku
—
EID výsledku v databázi Scopus
2-s2.0-105011093219