Zobrazeno 1 - 10
of 2 127
pro vyhledávání: '"Traffic flow prediction"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-24 (2024)
Abstract With the advancement of modern UAV technology, UAVs have become integral to creating traffic management monitoring systems. Additionally, UAV-based traffic monitoring systems can predict traffic flow by integrating machine learning methods.
Externí odkaz:
https://doaj.org/article/e7dca9e58204412e9c39836ef992db34
Publikováno v:
IET Intelligent Transport Systems, Vol 18, Iss 11, Pp 2097-2113 (2024)
Abstract In order to further improve the accuracy of short‐term traffic flow prediction on designated sections of highways, a combined prediction model is designed in this paper to predict the traffic flow on designated sections of highways. Firstl
Externí odkaz:
https://doaj.org/article/469ccf0847064dc6a5ad43e82db089d3
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract The traffic flow prediction is the key to alleviate traffic congestion, yet very challenging due to the complex influence factors. Currently, the most of deep learning models are designed to dig out the intricate dependency in continuous sta
Externí odkaz:
https://doaj.org/article/c2fe98e0cf8a4cbfb7834326bc536244
Autor:
Sunkara Teena Mrudula, Meenakshi, Mahyudin Ritonga, S. Sivakumar, Malik Jawarneh, Sammy F, T. Keerthika, Kantilal Pitambar Rane, Bhaskar Roy
Publikováno v:
Measurement: Sensors, Vol 35, Iss , Pp 101297- (2024)
The rapid expansion of urban areas and the increasing number of vehicles on the road have resulted in accidents, traffic congestion, economic repercussions, environmental deterioration, and excessive fuel consumption. A dependable traffic management
Externí odkaz:
https://doaj.org/article/f2beee294cdf4d808de5614ba698a3e4
Publikováno v:
Results in Engineering, Vol 23, Iss , Pp 102342- (2024)
Precise traffic flow prediction is a central component of advancing intelligent transportation systems, providing essential insights for optimizing traffic management, reducing travel times, and alleviating congestion. This study introduces an effici
Externí odkaz:
https://doaj.org/article/43ec22ced46046ca996fb3244b0ed374
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 17, Iss 1, Pp 1-18 (2024)
Abstract With the development of society and the advancement of urbanization, the development of intelligent transportation system has attracted much attention. Efficient and accurate traffic flow prediction is one of the core tasks in the research o
Externí odkaz:
https://doaj.org/article/e86f0a85544c4e42bdd73d60923b8fe9
Publikováno v:
Big Data Mining and Analytics, Vol 7, Iss 1, Pp 171-187 (2024)
Accurate and efficient urban traffic flow prediction can help drivers identify road traffic conditions in real-time, consequently helping them avoid congestion and accidents to a certain extent. However, the existing methods for real-time urban traff
Externí odkaz:
https://doaj.org/article/c890b1b182b44e5cb62244332f5163f6
Publikováno v:
Transportation Engineering, Vol 18, Iss , Pp 100279- (2024)
Efficiently extracting and analyzing large urban traffic data, accurately predicting traffic conditions, and improving urban traffic management require careful selection of an appropriate data sample size. The suitable size of data sample assumes par
Externí odkaz:
https://doaj.org/article/149c3e5b808b45dea46773d5bbd6be7e
Publikováno v:
Systems Science & Control Engineering, Vol 12, Iss 1 (2024)
This paper proposes a novel phase-based short-term traffic flow prediction method based on parallel multi-task learning for isolated intersections. Different from traditional short-term traffic flow prediction methods, we take the traffic flow of eac
Externí odkaz:
https://doaj.org/article/26e88d86c3b840cb82fd1d90d88dfed7
Publikováno v:
IEEE Access, Vol 12, Pp 138372-138385 (2024)
Accurate understanding of maritime traffic flow is crucial for optimizing waterway and port resources. However, the complex spatiotemporal characteristics and non-stationary sequences in maritime traffic pose challenges for feature extraction. This s
Externí odkaz:
https://doaj.org/article/9223291645aa4157b663c3ecdbdd7ad1