Title :
Study on forecasting method of highway port cargo volume
Author :
Shengling, Xiao ; Wei, Wang ; Bo, Wang
Author_Institution :
Coll. of Eng. & Technol., Northeast Forestry Univ., Harbin, China
Abstract :
According to the problem of predicting highway port freight volume, the BP neural network combination forecasting model is proposed based on the study of commonly used forecasting methods including time series forecast, gray system forecast and combination forecast method. Combined with the freight traffic condition of Suifenhe highway port, the combination forecasting model is verified. The experimental results indicate that this method is very effective to forecast the highway freight.
Keywords :
backpropagation; forecasting theory; freight handling; goods distribution; grey systems; production engineering computing; road traffic; time series; BP neural network; Suifenhe highway port; combination forecast; forecasting method; freight traffic condition; gray system forecast; highway port cargo volume; highway port freight volume; time series forecast; Equations; Neural networks; Prediction methods; Predictive models; Regression analysis; Road transportation; Smoothing methods; Technology forecasting; Telecommunication traffic; Testing; BP Neural Network; Combination Forecasting; Freight Traffic Volume;
Conference_Titel :
Logistics Systems and Intelligent Management, 2010 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4244-7331-1
DOI :
10.1109/ICLSIM.2010.5461327
