Based on Combined Model of Refined Oil Sales Forecast

Abstract:

Refined oil is the base of national industrial, as a class of strategic commodities, it occupies an important position in national economy. In this paper, the elastic coefficient method, trend extrapolation and gray theory prediction model was adopted to forecast sales volume of refined oil based on an example, and each prediction model error was analyzed. Finally based on the three models, a combination forecasting model was established, which each models weight is determined by the relative weights of the error. The combination forecasting method makes error decrease and more accurate. Forecasting methods used in this paper can enhance oil sales volume forecast and improve the overall efficiency of sales system foundation.

• Periodical: Applied Mechanics and Materials (Volumes 448-453)
• Pages: 4262-4266
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.448-453.4262
• Online since: October 2013
• Authors: Yuan Hai Liu*, Huang Kun, Yan Xian, Yi Tang Lv
• Keywords: Combination Forecasting Model, Elasticity Coefficient Method, Gray Theory, Sales of Refined Oil, Trend Extrapolation

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