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Study of Railway Track Irregularity Standard Deviation Time Series Based on Data Mining and Linear Model
- Source :
- Mathematical Problems in Engineering, Vol 2013 (2013)
- Publication Year :
- 2013
- Publisher :
- Hindawi Limited, 2013.
-
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.
- Subjects :
- Engineering
Article Subject
Series (mathematics)
business.industry
lcsh:Mathematics
General Mathematics
media_common.quotation_subject
General Engineering
Linear model
ComputerApplications_COMPUTERSINOTHERSYSTEMS
lcsh:QA1-939
computer.software_genre
Track (rail transport)
Standard deviation
lcsh:TA1-2040
Service (economics)
Track geometry
Data mining
Time series
lcsh:Engineering (General). Civil engineering (General)
business
Cluster analysis
computer
media_common
Subjects
Details
- ISSN :
- 15635147 and 1024123X
- Volume :
- 2013
- Database :
- OpenAIRE
- Journal :
- Mathematical Problems in Engineering
- Accession number :
- edsair.doi.dedup.....b734a8387cbeb7939eb1af5b78302c0b