An improved gray prediction model for China's beef consumption forecasting.

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ID: 102236
2019
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Abstract
To balance the supply and demand in China's beef market, beef consumption must be scientifically and effectively forecasted. Beef consumption is affected by many factors and is characterized by gray uncertainty. Therefore, gray theory can be used to forecast the beef consumption, In this paper, the structural defects and unreasonable parameter design of the traditional gray model are analyzed. Then, a new gray model termed, EGM(1,1,r), is built, and the modeling conditions and error checking methods of EGM(1,1,r) are studied. Then, EGM(1,1,r) is used to simulate and forecast China's beef consumption. The results show that both the simulation and prediction precisions of the new model are better than those of other gray models. Finally, the new model is used to forecast China's beef consumption for the period from 2019-2025. The findings will serve as an important reference for the Chinese government in formulating policies to ensure the balance between the supply and demand for Chinese beef.
Reference Key
zeng2019anplos Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Zeng, Bo;Li, Shuliang;Meng, Wei;Zhang, Dehai;
Journal PloS one
Year 2019
DOI
10.1371/journal.pone.0221333
URL
Keywords
uncertainty risk aversion disaster management shelter location stochastic programming traffic assignment

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