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Study of Railway Track Irregularity Standard Deviation Time Series Based on Data Mining and Linear Model
Joint Authors
Xu, Weixiang
Wang, Hanning
Wei, Lili
Jia, Chaolong
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-10-21
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Good track geometry state ensures the safe operation of the railway passenger service and freight service.
Railway transportation plays an important role in the Chinese economic and social development.
This paper studies track irregularity standard deviation time series data and focuses on the characteristics and trend changes of track state by applying clustering analysis.
Linear recursive model and linear-ARMA model based on wavelet decomposition reconstruction are proposed, and all they offer supports for the safe management of railway transportation.
American Psychological Association (APA)
Jia, Chaolong& Xu, Weixiang& Wei, Lili& Wang, Hanning. 2013. Study of Railway Track Irregularity Standard Deviation Time Series Based on Data Mining and Linear Model. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-12.
https://search.emarefa.net/detail/BIM-1009545
Modern Language Association (MLA)
Jia, Chaolong…[et al.]. Study of Railway Track Irregularity Standard Deviation Time Series Based on Data Mining and Linear Model. Mathematical Problems in Engineering No. 2013 (2013), pp.1-12.
https://search.emarefa.net/detail/BIM-1009545
American Medical Association (AMA)
Jia, Chaolong& Xu, Weixiang& Wei, Lili& Wang, Hanning. Study of Railway Track Irregularity Standard Deviation Time Series Based on Data Mining and Linear Model. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-12.
https://search.emarefa.net/detail/BIM-1009545
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1009545