Title :
Study Oil logistics demand prediction based on grey system
Author_Institution :
Sch. of Bus. Adm., Guizhou Coll. of Finance & Econ., Guiyang, China
Abstract :
With the development of economics the demand of oil logistics has also rapidly increased, grasping the variation of oil companies´ logistics demand timely and accurately has a great significance on smooth operation of the national economy. This paper takes advantage of grey model of prediction quantitatively research on the logistics demand of oil companies, the examples show that the model of prediction has a higher accuracy.
Keywords :
demand forecasting; grey systems; industrial economics; logistics; petroleum industry; demand prediction; grey model; grey system; national economy; oil company; oil logistics; Companies; Demand forecasting; Economic forecasting; Educational institutions; Fuel economy; Logistics; Petroleum; Power generation economics; Predictive models; Random number generation; grey system; logistics demand; oil; prediction;
Conference_Titel :
Computer Design and Applications (ICCDA), 2010 International Conference on
Conference_Location :
Qinhuangdao
Print_ISBN :
978-1-4244-7164-5
Electronic_ISBN :
978-1-4244-7164-5
DOI :
10.1109/ICCDA.2010.5541286
