Demand Forecast of Emergency Supplies Based on Gray Model

DOI

10.2991/ameii-15.2015.250How to use a DOI?

Keywords

Gray Model; Demand Forecast; GM (0; 3) Model.

Abstract

This article focuses on the study of the difficult demand forecast of emergency supplies during the emergency relief process. To resolve the limit that there are few parameters available in the emergency relief scene, a gray forecast model with fewer parameters inputted is raised for this issue. To start, the demand forecast of materials is transformed into the predicted deaths, and factors influencing the deaths are analyzed by using the gray degree of association model. The ratio of deaths and local population and mortality are the system characteristic variables of this issue, moreover, rate of housing collapse, GDP, seismic intensity level, Per capita GDP of the affected region, and other parameters are proposed as system related factors variables. Then modeling through gray degree of association, gray relational coefficient and correlation degree are obtained. During the process of forecast, rate of housing collapse and seismic intensity level are regarded as impact factors. Together with the mortality, these three factors make up the GM (0, 3) model. There is overwhelming advantage in proving the gray forecast model applied in selecting model reference factors and solving the forecast value. Combining the features of gray-scale theory, a fairly large historical data are no more needed. It is clear that a great improvement has been witnessed compared with other traditional model.

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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TY  - CONF
AU  - Xi Chen
AU  - Zhao Liu
PY  - 2015/04
DA  - 2015/04
TI  - Demand Forecast of Emergency Supplies Based on Gray Model
BT  - Proceedings of the International Conference on Advances in Mechanical Engineering and Industrial Informatics
PB  - Atlantis Press
SP  - 1357
EP  - 1361
SN  - 2352-5401
UR  - https://doi.org/10.2991/ameii-15.2015.250
DO  - 10.2991/ameii-15.2015.250
ID  - Chen2015/04
ER  -