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Multistep-Ahead Air Passengers Traffic Prediction with Hybrid ARIMA-SVMs Models
Joint Authors
Xiong, Tao
Ming, Wei
Hu, Zhongyi
Bao, Yukun
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-02-27
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
The hybrid ARIMA-SVMs prediction models have been established recently, which take advantage of the unique strength of ARIMA and SVMs models in linear and nonlinear modeling, respectively.
Built upon this hybrid ARIMA-SVMs models alike, this study goes further to extend them into the case of multistep-ahead prediction for air passengers traffic with the two most commonly used multistep-ahead prediction strategies, that is, iterated strategy and direct strategy.
Additionally, the effectiveness of data preprocessing approaches, such as deseasonalization and detrending, is investigated and proofed along with the two strategies.
Real data sets including four selected airlines’ monthly series were collected to justify the effectiveness of the proposed approach.
Empirical results demonstrate that the direct strategy performs better than iterative one in long term prediction case while iterative one performs better in the case of short term prediction.
Furthermore, both deseasonalization and detrending can significantly improve the prediction accuracy for both strategies, indicating the necessity of data preprocessing.
As such, this study contributes as a full reference to the planners from air transportation industries on how to tackle multistep-ahead prediction tasks in the implementation of either prediction strategy.
American Psychological Association (APA)
Ming, Wei& Bao, Yukun& Hu, Zhongyi& Xiong, Tao. 2014. Multistep-Ahead Air Passengers Traffic Prediction with Hybrid ARIMA-SVMs Models. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-14.
https://search.emarefa.net/detail/BIM-1050129
Modern Language Association (MLA)
Ming, Wei…[et al.]. Multistep-Ahead Air Passengers Traffic Prediction with Hybrid ARIMA-SVMs Models. The Scientific World Journal No. 2014 (2014), pp.1-14.
https://search.emarefa.net/detail/BIM-1050129
American Medical Association (AMA)
Ming, Wei& Bao, Yukun& Hu, Zhongyi& Xiong, Tao. Multistep-Ahead Air Passengers Traffic Prediction with Hybrid ARIMA-SVMs Models. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-14.
https://search.emarefa.net/detail/BIM-1050129
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1050129