Traffic Flow Prediction Model for Large-Scale Road Network Based on Cloud Computing
Joint Authors
Zhou, Hu-Xing
Mei, Duo
Yang, Qingfang
Li, Xiaowen
Yang, Zhao-Sheng
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-08-12
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
To increase the efficiency and precision of large-scale road network traffic flow prediction, a genetic algorithm-support vector machine (GA-SVM) model based on cloud computing is proposed in this paper, which is based on the analysis of the characteristics and defects of genetic algorithm and support vector machine.
In cloud computing environment, firstly, SVM parameters are optimized by the parallel genetic algorithm, and then this optimized parallel SVM model is used to predict traffic flow.
On the basis of the traffic flow data of Haizhu District in Guangzhou City, the proposed model was verified and compared with the serial GA-SVM model and parallel GA-SVM model based on MPI (message passing interface).
The results demonstrate that the parallel GA-SVM model based on cloud computing has higher prediction accuracy, shorter running time, and higher speedup.
American Psychological Association (APA)
Yang, Zhao-Sheng& Mei, Duo& Yang, Qingfang& Zhou, Hu-Xing& Li, Xiaowen. 2014. Traffic Flow Prediction Model for Large-Scale Road Network Based on Cloud Computing. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-508662
Modern Language Association (MLA)
Yang, Zhao-Sheng…[et al.]. Traffic Flow Prediction Model for Large-Scale Road Network Based on Cloud Computing. Mathematical Problems in Engineering No. 2014 (2014), pp.1-8.
https://search.emarefa.net/detail/BIM-508662
American Medical Association (AMA)
Yang, Zhao-Sheng& Mei, Duo& Yang, Qingfang& Zhou, Hu-Xing& Li, Xiaowen. Traffic Flow Prediction Model for Large-Scale Road Network Based on Cloud Computing. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-508662
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-508662