TRAFFIC ACCIDENT RISK CLASSIFICATION USING NEURAL NETWORKS

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21260%2F21%3A00353998" target="_blank" >RIV/68407700:21260/21:00353998 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.14311/nnw.2021.31.019" target="_blank" >https://doi.org/10.14311/nnw.2021.31.019</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.14311/nnw.2021.31.019" target="_blank" >10.14311/nnw.2021.31.019</a>

Jazyk výsledku

angličtina

Název v původním jazyce

TRAFFIC ACCIDENT RISK CLASSIFICATION USING NEURAL NETWORKS

Popis výsledku v původním jazyce

The article deals with the current issue of traffic accident risk classification in urban area. In connection with the increase in traffic in the Czech Republic, a higher probability of risks of traffic excesses can be expected in the future. If there is a traffic excess in the city, the aim is to propose a meaningful traffic management solution to minimize the social losses. The main needs are the early identification and classification of the cause of the traffic excess, finding a suitable alternative solution, quick application of that solution, and the rapid ability to resume operations in the area of congestion. Traffic prediction is one of the tools for the early identification of traffic excess. The article describes extensive research focused on the classification and prediction of the output variable of accident risk based on own programmed neural networks. The research outputs will be subsequently used for the creation of a traffic application for a selected urban area in the Czech Republic

Název v anglickém jazyce

TRAFFIC ACCIDENT RISK CLASSIFICATION USING NEURAL NETWORKS

Popis výsledku anglicky

The article deals with the current issue of traffic accident risk classification in urban area. In connection with the increase in traffic in the Czech Republic, a higher probability of risks of traffic excesses can be expected in the future. If there is a traffic excess in the city, the aim is to propose a meaningful traffic management solution to minimize the social losses. The main needs are the early identification and classification of the cause of the traffic excess, finding a suitable alternative solution, quick application of that solution, and the rapid ability to resume operations in the area of congestion. Traffic prediction is one of the tools for the early identification of traffic excess. The article describes extensive research focused on the classification and prediction of the output variable of accident risk based on own programmed neural networks. The research outputs will be subsequently used for the creation of a traffic application for a selected urban area in the Czech Republic

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

21100 - Other engineering and technologies

Projekt

<a href="/cs/project/TJ01000183" target="_blank" >TJ01000183: Predikce dopravních excesů využívající neuronové sítě</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Neural Network World

ISSN

1210-0552

e-ISSN

2336-4335

Svazek periodika

31

Číslo periodika v rámci svazku

05/21

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

11

Strana od-do

343-353

Kód UT WoS článku

000739166400003

EID výsledku v databázi Scopus

2-s2.0-85123348014