DocumentCode :
3262628
Title :
Prediction of freight quantity for the multiple regression method
Author :
Shejun, Deng ; Jun, Chen
Author_Institution :
Transp. Coll., Southeast Univ., Nanjing, China
fYear :
2011
fDate :
22-24 April 2011
Firstpage :
5263
Lastpage :
5266
Abstract :
The multiple regression method is commonly used in the freight quantity prediction because of its simple and easy. How to establish the prediction model is a question worthy of being discussed, when we want to improve the precision according to different types of cities and independent variables. This paper analysed the character of industrial structure and discovered the rule of freight quantity and unit GDP freight quantity by the example of the city Yangzhou. The paper established two prediction models by the ways of multianalysis. The first model was the relationships between freight quantity and some independent variables including Social consumable retail turnover, GDP, the first industrial value of outputs the second industrial value of output and the third industrial value of output; The second model was the relationships between unit GDP freight quantity and other independent variables including the scale of the first industry, the scale of the second industry and the scale of the third industry. Finally, the first model was proved to be more practicality and better on application in contrast with the second one in forecasting of freight quantity.
Keywords :
freight handling; regression analysis; retailing; GDP freight quantity; industrial structure; multiple regression method; social consumable retail turnover; Cities and towns; Economic indicators; Educational institutions; Industries; Predictive models; Roads; freight quantity; freight quantity prediction; model; multiple regression method; unit GDP;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electric Technology and Civil Engineering (ICETCE), 2011 International Conference on
Conference_Location :
Lushan
Print_ISBN :
978-1-4577-0289-1
Type :
conf
DOI :
10.1109/ICETCE.2011.5776510
Filename :
5776510
Link To Document :
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