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Urban Traffic Flow Prediction Model with CPSOSSVM Algorithm under the Edge Computing Framework
Joint Authors
An, Xingshuo
Liu, Fengkai
Ma, Xingmin
Liang, Guangnan
Source
Wireless Communications and Mobile Computing
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-09-01
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Information Technology and Computer Science
Abstract EN
Urban traffic flow prediction has always been an important realm for smart city build-up.
With the development of edge computing technology in recent years, the network edge nodes of smart cities are able to collect and process various types of urban traffic data in real time, which leads to the possibility of deploying intelligent traffic prediction technology with real-time analysis and timely feedback on the edge.
In view of the strong nonlinear characteristics of urban traffic flow, multiple dynamic and static influencing factors involved, and increasing difficulty of short-term traffic flow prediction in a metropolitan area, this paper proposes an urban traffic flow prediction model based on chaotic particle swarm optimization algorithm-smooth support vector machine (CPSO/SSVM).
The prediction model has built a new second-order smooth function to achieve better approximation and regression effects and has further improved the computational efficiency of the smooth support vector machine algorithm through chaotic particle swarm optimization.
Simulation experiment results show that this model can accurately predict urban traffic flow.
American Psychological Association (APA)
Liu, Fengkai& Ma, Xingmin& An, Xingshuo& Liang, Guangnan. 2020. Urban Traffic Flow Prediction Model with CPSOSSVM Algorithm under the Edge Computing Framework. Wireless Communications and Mobile Computing،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1214823
Modern Language Association (MLA)
Liu, Fengkai…[et al.]. Urban Traffic Flow Prediction Model with CPSOSSVM Algorithm under the Edge Computing Framework. Wireless Communications and Mobile Computing No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1214823
American Medical Association (AMA)
Liu, Fengkai& Ma, Xingmin& An, Xingshuo& Liang, Guangnan. Urban Traffic Flow Prediction Model with CPSOSSVM Algorithm under the Edge Computing Framework. Wireless Communications and Mobile Computing. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1214823
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1214823