Forecasting and Analysis of Agricultural Product Logistics Demand in Tibet Based on Combination Forecasting Model

Over the years, the logistics development in Tibet has fallen behind the transport. Since the opening of Qinghai-Tibet Railway in 2006, the opportunity for development of modern logistics has been brought to Tibet. The logistics demand analysis and forecasting is a prerequisite for regional logistics planning. By establishing indicator system for logistics demand of agricultural products, agricultural product logistics principal component regression model, gray forecasting model, BP neural network forecasting model are built. Because of the single model’s limitations, quadratic-linear programming model is used to build combination forecasting model to predict the logistics demand scale of agricultural products in Tibet over the next five years. The empirical analysis results show that combination forecasting model is superior to single forecasting model, and it has higher precision, so combination forecasting model will have much wider application foreground and development potential in the field of logistics.


Subject(s):
Issue Date:
2015-09
Publication Type:
Journal Article
PURL Identifier:
http://purl.umn.edu/212537
Published in:
Volume 07, Issue 09
Asian Agricultural Research
Page range:
17-27
Total Pages:
7




 Record created 2017-04-01, last modified 2017-08-28

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