Track Irregularity Time Series Analysis and Trend Forecasting
Joint Authors
Wang, Futian
Xu, Weixiang
Wang, Hanning
Jia, Chaolong
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-12-04
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
The combination of linear and nonlinear methods is widely used in the prediction of time series data.
This paper analyzes track irregularity time series data by using gray incidence degree models and methods of data transformation, trying to find the connotative relationship between the time series data.
In this paper, GM (1,1) is based on first-order, single variable linear differential equations; after an adaptive improvement and error correction, it is used to predict the long-term changing trend of track irregularity at a fixed measuring point; the stochastic linear AR, Kalman filtering model, and artificial neural network model are applied to predict the short-term changing trend of track irregularity at unit section.
Both long-term and short-term changes prove that the model is effective and can achieve the expected accuracy.
American Psychological Association (APA)
Jia, Chaolong& Xu, Weixiang& Wang, Futian& Wang, Hanning. 2012. Track Irregularity Time Series Analysis and Trend Forecasting. Discrete Dynamics in Nature and Society،Vol. 2012, no. 2012, pp.1-15.
https://search.emarefa.net/detail/BIM-468178
Modern Language Association (MLA)
Jia, Chaolong…[et al.]. Track Irregularity Time Series Analysis and Trend Forecasting. Discrete Dynamics in Nature and Society No. 2012 (2012), pp.1-15.
https://search.emarefa.net/detail/BIM-468178
American Medical Association (AMA)
Jia, Chaolong& Xu, Weixiang& Wang, Futian& Wang, Hanning. Track Irregularity Time Series Analysis and Trend Forecasting. Discrete Dynamics in Nature and Society. 2012. Vol. 2012, no. 2012, pp.1-15.
https://search.emarefa.net/detail/BIM-468178
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-468178