Proceedings of the 2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS 2017)

Analysis of Civil Aviation's Passenger Turnover Based on X11-ARIMA Model

Authors
Lixin Zhang, Cuifang Yang
Corresponding Author
Lixin Zhang
Available Online November 2017.
DOI
10.2991/amms-17.2017.46How to use a DOI?
Keywords
turnover; long-term trend; sequence
Abstract

The analysis of civil aviation's passenger turnover is of great significance to civil aviation department. According to the data of civil aviation's passenger turnover in the last 12 years, using the X11 method, the long-term trend was separated, and the results showed that the civil aviation's passenger turnover was linearly increasing and there was a seasonal effect of one year cycle. Using the difference method to eliminate the influence of long-term trend and seasonal effect, ARIMA model was proposed to fit the development of the sequence. Taking the data from January to September in 2017 as the test sample, the model predicted the data very precisely.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS 2017)
Series
Advances in Intelligent Systems Research
Publication Date
November 2017
ISBN
978-94-6252-433-0
ISSN
1951-6851
DOI
10.2991/amms-17.2017.46How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Lixin Zhang
AU  - Cuifang Yang
PY  - 2017/11
DA  - 2017/11
TI  - Analysis of Civil Aviation's Passenger Turnover Based on X11-ARIMA Model
BT  - Proceedings of the 2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS 2017)
PB  - Atlantis Press
SP  - 207
EP  - 210
SN  - 1951-6851
UR  - https://doi.org/10.2991/amms-17.2017.46
DO  - 10.2991/amms-17.2017.46
ID  - Zhang2017/11
ER  -