A fuzzy method for predicting the demand for rail freight transportation

Wong, Wing-gun, Niu, H.M., & Ferreira, Luis (2003) A fuzzy method for predicting the demand for rail freight transportation. Journal of Advanced Transportation, 37(2), pp. 159-171.

PDF (31kB)


The demand for rail freight transportation is a continuosly changing process over space and time and is affected by many quantitative and qualitative factors. In order to develop a more rational transport planning process to be followed by railway organisations, there is a need to accurately forecast freight demand under a dynamic and uncertain environment.. In conventional linear regression analysis, the deviations between the observed and the estimated values are supposed to be due to observation errors. In this paper, taking a different perspective, these deviations are regarded as the non-random uncertainties associated with forecasting issues.The details of fuzzy linear regression method are put forward and discussed in the paper. Based on an analyzes of the characteristics of the rail transportation problem, the proposed model was successfully applied to a real example from China.The results of that application are also presented here.

Impact and interest:

1 citations in Scopus
Search Google Scholar™
1 citations in Web of Science®

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

1,397 since deposited on 06 Dec 2005
51 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 2767
Item Type: Journal Article
Refereed: Yes
Additional Information: e-mail: cewgwong@polyu.edu.hk
Additional URLs:
Keywords: Fuzzy method, Linear regression analysis, Freight transportation demand
ISSN: 0197-6729
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > CIVIL ENGINEERING (090500) > Transport Engineering (090507)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Copyright Owner: Copyright 2003 Institute for Transportation (Canada)
Deposited On: 06 Dec 2005 00:00
Last Modified: 09 Jun 2010 12:28

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page