An Imputation Method for Missing Traffic Data Based on FCM Optimized by PSO-SVR
Joint Authors
Shang, Qiang
Tan, Derong
Gao, Song
Yang, Zhao-Sheng
Source
Journal of Advanced Transportation
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-21, 21 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-01-08
Country of Publication
Egypt
No. of Pages
21
Main Subjects
Abstract EN
Missing traffic data are inevitable due to detector failure or communication failure.
Currently, most of imputation methods estimated the missing traffic values by using spatial-temporal information as much as possible.
However, it ignores an important fact that spatial-temporal information of the traffic missing data is often incomplete and unavailable.
Moreover, most of the existing methods are verified by traffic data from freeway, and their applicability to urban road data needs to be further verified.
In this paper, a hybrid method for missing traffic data imputation is proposed using FCM optimized by a combination of PSO algorithm and SVR.
In this method, FCM is the basic algorithm and the parameters of FCM are optimized.
Firstly, the patterns of missing traffic data are analyzed and the representation of missing traffic data is given using matrix-based data structure.
Then, traffic data from urban expressway and urban arterial road are used to analyze spatial-temporal correlation of the traffic data for the determination of the proposed method input.
Finally, numerical experiment is designed from three perspectives to test the performance of the proposed method.
The experimental results demonstrate that the novel method not only has high imputation precision, but also exhibits good robustness.
American Psychological Association (APA)
Shang, Qiang& Yang, Zhao-Sheng& Gao, Song& Tan, Derong. 2018. An Imputation Method for Missing Traffic Data Based on FCM Optimized by PSO-SVR. Journal of Advanced Transportation،Vol. 2018, no. 2018, pp.1-21.
https://search.emarefa.net/detail/BIM-1181107
Modern Language Association (MLA)
Shang, Qiang…[et al.]. An Imputation Method for Missing Traffic Data Based on FCM Optimized by PSO-SVR. Journal of Advanced Transportation No. 2018 (2018), pp.1-21.
https://search.emarefa.net/detail/BIM-1181107
American Medical Association (AMA)
Shang, Qiang& Yang, Zhao-Sheng& Gao, Song& Tan, Derong. An Imputation Method for Missing Traffic Data Based on FCM Optimized by PSO-SVR. Journal of Advanced Transportation. 2018. Vol. 2018, no. 2018, pp.1-21.
https://search.emarefa.net/detail/BIM-1181107
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1181107