@inproceedings{6e8bf84aa7bb4ec3a3d0774c31a8058a,
title = "Forecasting freight volume based on an entropy combination method",
abstract = "Freight volume forecasting is essential for transportation network planning, construction and management. However, it is generally difficult to forecast the freight volume accurately by using any single method. Combination method can effectively improve forecasting accuracy, and consequently is widely utilized. Based on the entropy theory, a parallel grey neural network combination model is constructed to forecast freight volume. The effectiveness and feasibility of the entropy combination method is demonstrated by a numerical example provided.",
keywords = "Entropy methods, Forecasting, Freight transportation",
author = "Liu, \{Xiao Feng\} and Daniel Sun and Du, \{Rong Yi\} and Peng, \{Zhong Ren\}",
year = "2010",
doi = "10.1061/41127(382)122",
language = "English",
isbn = "9780784411278",
series = "ICCTP 2010: Integrated Transportation Systems: Green, Intelligent, Reliable - Proceedings of the 10th International Conference of Chinese Transportation Professionals",
pages = "1143--1148",
booktitle = "ICCTP 2010",
note = "10th International Conference of Chinese Transportation Professionals - Integrated Transportation Systems: Green, Intelligent, Reliable, ICCTP 2010 ; Conference date: 04-08-2010 Through 08-08-2010",
}