Proceedings of the First International Conference on Information Sciences, Machinery, Materials and Energy

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Aircraft Spareparts Demand Forecasting based on Multiple ARIMA Model

Authors
Houju Xin, Yang Cui, Xinbin Liu, Shujian Luo
Corresponding Author
Houju Xin
Available Online July 2015.
DOI
10.2991/icismme-15.2015.154How to use a DOI?
Keywords
Time Series; Demand forecasting; Parameter estimation; White noise sequence.
Abstract

In order to predict the uncertain demand for aircraft spare parts, a multiple ARIMA model is used to solve this problem by time series forecasting system in SPSS. The prediction result and its applications are discussed. This method is simple, practical and convenient for spreading.

Copyright
© 2015, 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 First International Conference on Information Sciences, Machinery, Materials and Energy
Series
Advances in Intelligent Systems Research
Publication Date
July 2015
ISBN
10.2991/icismme-15.2015.154
ISSN
1951-6851
DOI
10.2991/icismme-15.2015.154How to use a DOI?
Copyright
© 2015, 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

risenwbib
TY  - CONF
AU  - Houju Xin
AU  - Yang Cui
AU  - Xinbin Liu
AU  - Shujian Luo
PY  - 2015/07
DA  - 2015/07
TI  - Aircraft Spareparts Demand Forecasting based on Multiple ARIMA Model
BT  - Proceedings of the First International Conference on Information Sciences, Machinery, Materials and Energy
PB  - Atlantis Press
SP  - 743
EP  - 746
SN  - 1951-6851
UR  - https://doi.org/10.2991/icismme-15.2015.154
DO  - 10.2991/icismme-15.2015.154
ID  - Xin2015/07
ER  -