Zobrazeno 1 - 10
of 2 077
pro vyhledávání: '"traffic data"'
Publikováno v:
ICT Express, Vol 10, Iss 6, Pp 1186-1198 (2024)
Nowadays, the rise in traffic density derived from the population growth in urban areas, has resulted in more traffic congestion. Despite advancements in Intelligent Transportation Systems (ITS), this still remains a considerable challenge. In this s
Externí odkaz:
https://doaj.org/article/0554f8dd3f154dbd857c68556f4c68f9
Autor:
Abilpatta Yerkanat, Voženílek Vít
Publikováno v:
Miscellanea Geographica: Regional Studies on Development, Vol 28, Iss 3, Pp 112-126 (2024)
The paper explores the substantial decline in European air transport during 2020, while employing interactive maps for visual analysis. According to the International Civil Aviation Organization’s (2020) economic analysis, there was a sharp 60% glo
Externí odkaz:
https://doaj.org/article/4b1cf4e317494304943da432f8f47bc2
Autor:
Iván Gómez, Sergio Ilarri
Publikováno v:
Data in Brief, Vol 57, Iss , Pp 110878- (2024)
The proliferation of urban areas and the concurrent increase in vehicular mobility have escalated the urgency for advanced traffic management solutions. This data article introduces two traffic datasets from Madrid, collected between June 2022 and Fe
Externí odkaz:
https://doaj.org/article/b3f319b967064e6f8c62754bff27aae1
Publikováno v:
Systems Science & Control Engineering, Vol 12, Iss 1 (2024)
In response to the problem of missing traffic flow data on highways, to solve the problem of insufficient mining of traffic flow characteristics using existing spatiotemporal correlation repair methods, a missing data repair method based on spatiotem
Externí odkaz:
https://doaj.org/article/f6ddc9d04c014c2fbfb835a590014ef6
Publikováno v:
PeerJ Computer Science, Vol 10, p e2408 (2024)
Traffic data imputation is crucial for the reliability and efficiency of intelligent transportation systems (ITSs), forming the foundation for downstream tasks like traffic prediction and management. However, existing deep learning-based imputation m
Externí odkaz:
https://doaj.org/article/1cc3456854b045f292ec2813bedd2fa4
Publikováno v:
Frontiers in Physics, Vol 12 (2024)
IntroductionAs 5G networks become widespread and their application scenarios expand, massive amounts of traffic data are continuously generated. Properly analyzing this data is crucial for enhancing 5G services.MethodsThis paper uses the visibility g
Externí odkaz:
https://doaj.org/article/8bfb452a934e4818b55cca75300aaba2
Autor:
Sulaimon, Ismail Abiodun, Alaka, Hafiz, Olu-Ajayi, Razak, Ahmad, Mubashir, Ajayi, Saheed, Hye, Abdul
Publikováno v:
Journal of Engineering, Design and Technology, 2022, Vol. 22, Issue 3, pp. 1030-1056.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/JEDT-10-2021-0554
Autor:
Samer Nofal
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-21 (2024)
Abstract We investigate if the vehicle travel time after 6 h on a given street can be predicted, provided the hourly vehicle travel time on the street in the last 19 h. Likewise, we examine if the traffic status (i.e., low, mild, or high) after 6 h o
Externí odkaz:
https://doaj.org/article/9d1d72cfc84c41bd9dd5c7608ef86a80
Publikováno v:
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), Vol 18, Iss 3 (2024)
Abstract The proliferation of cyber security attacks necessitates advanced and efficient detection methods. This study explores the application of Convolutional Neural Networks (CNNs) for classifying cyber security attacks using a comprehensive datas
Externí odkaz:
https://doaj.org/article/ead2ba90d7514bc7bca44b73fbf46bec
Publikováno v:
Data Science and Engineering, Vol 9, Iss 3, Pp 341-359 (2024)
Abstract With the exponential increase in the urban population, urban transportation systems are confronted with numerous challenges. Traffic congestion is common, traffic accidents happen frequently, and traffic environments are deteriorating. To al
Externí odkaz:
https://doaj.org/article/b41bffdd7fb44eaf89ad8f835be098e0