A fuzzy method for predicting the demand for rail freight transportation

Wong, WG, Niu, H and Ferreira, L (2003) A fuzzy method for predicting the demand for rail freight transportation. Journal of Advanced Transportation, 37 2: 159-171.

Author Wong, WG
Niu, H
Ferreira, L
Title A fuzzy method for predicting the demand for rail freight transportation
Journal name Journal of Advanced Transportation   Check publisher's open access policy
ISSN 0197-6729
Publication date 2003-04
Sub-type Article (original research)
Volume 37
Issue 2
Start page 159
End page 171
Total pages 13
Place of publication North Carolina
Publisher Durham
Language eng
Subject 12 Built Environment and Design
1204 Engineering Design
1205 Urban and Regional Planning
120506 Transport Planning
Abstract The demand for rail freight transportation is a continuously 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 organizations, 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 fuzziness of the system’s structure. 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.
Keyword Linear regression analysis
Freight transportation
Transport planning
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Unknown

Document type: Journal Article
Sub-type: Article (original research)
Collections: Excellence in Research Australia (ERA) - Collection
School of Civil Engineering Publications
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Created: Mon, 16 Nov 2009, 08:31:16 EST