Research and Practice of Tobacco Industrial Companies' Sales Forecast Based on ARMA Model, Seasonal Fluctuation and Policy Factor

DOI

10.2991/aiie-16.2016.126How to use a DOI?

Keywords

ARMA; autoregressive; moving average; policy influence; seasonal forecasting; tobacco; sales forecast

Abstract

In the wave of marketization reform, the tobacco industry has been gradually transforming to the market-driven planning model from fully planned economic model. In the tobacco market demand forecast, multiple reasons have been showing impact on each other like industry's own growth, seasonal fluctuations, policy impact etc. It's an industry challenge for many tobacco companies to provide rational, reliable and accurate prediction of sales trends. This essay, based on Zhejiang Tobacco's actual needs, established a hybrid tobacco sales forecast model based on Autoregressive Moving Average (ARMA) algorithm as well as taking seasonal fluctuations and policy influence into account. This model is validated in the simulation process.

Copyright

© 2016, 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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TY  - CONF
AU  - Qiao Shi
AU  - Yong Cen
AU  - Liping Xu
AU  - Lina Zhang
PY  - 2016/11
DA  - 2016/11
TI  - Research and Practice of Tobacco Industrial Companies' Sales Forecast Based on ARMA Model, Seasonal Fluctuation and Policy Factor
BT  - Proceedings of the 2016 2nd International Conference on Artificial Intelligence and Industrial Engineering (AIIE 2016)
PB  - Atlantis Press
SP  - 546
EP  - 551
SN  - 1951-6851
UR  - https://doi.org/10.2991/aiie-16.2016.126
DO  - 10.2991/aiie-16.2016.126
ID  - Shi2016/11
ER  -