Multidimensional Scaling-Based Data Dimension Reduction Method for Application in Short-Term Traffic Flow Prediction for Urban Road Network
Joint Authors
Zhao, Yi
Ukkusuri, Satish V.
Lu, Jian
Source
Journal of Advanced Transportation
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-11-19
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
This study develops a multidimensional scaling- (MDS-) based data dimension reduction method.
The method is applied to short-term traffic flow prediction in urban road networks.
The data dimension reduction method can be divided into three steps.
The first is data selection based on qualitative analysis, the second is data grouping using the MDS method, and the last is data dimension reduction based on a correlation coefficient.
Backpropagation neural network (BPNN) and multiple linear regression (MLR) models are employed in four kinds of urban traffic environments to test whether the proposed method improves the prediction accuracy of traffic flow.
The results show that prediction models using traffic data after dimension reduction outperform the same prediction models using other datasets.
The proposed method provides an alternative to existing models for urban traffic prediction.
American Psychological Association (APA)
Zhao, Yi& Ukkusuri, Satish V.& Lu, Jian. 2018. Multidimensional Scaling-Based Data Dimension Reduction Method for Application in Short-Term Traffic Flow Prediction for Urban Road Network. Journal of Advanced Transportation،Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1181205
Modern Language Association (MLA)
Zhao, Yi…[et al.]. Multidimensional Scaling-Based Data Dimension Reduction Method for Application in Short-Term Traffic Flow Prediction for Urban Road Network. Journal of Advanced Transportation No. 2018 (2018), pp.1-10.
https://search.emarefa.net/detail/BIM-1181205
American Medical Association (AMA)
Zhao, Yi& Ukkusuri, Satish V.& Lu, Jian. Multidimensional Scaling-Based Data Dimension Reduction Method for Application in Short-Term Traffic Flow Prediction for Urban Road Network. Journal of Advanced Transportation. 2018. Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1181205
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1181205