Study of Railway Track Irregularity Standard Deviation Time Series Based on Data Mining and Linear Model
Jia Chaolong,
Xu Weixiang,
Wei Lili and
Wang Hanning
Mathematical Problems in Engineering, 2013, vol. 2013, 1-12
Abstract:
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.
Date: 2013
References: Add references at CitEc
Citations:
Downloads: (external link)
http://downloads.hindawi.com/journals/MPE/2013/486738.pdf (application/pdf)
http://downloads.hindawi.com/journals/MPE/2013/486738.xml (text/xml)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:486738
DOI: 10.1155/2013/486738
Access Statistics for this article
More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().