Open AccessA fuzzy method for predicting the demand for rail freight transportation
Author(s) -
Wong W. G.,
Niu H.,
Ferreira L.
Publication year - 2003
Publication title -
journal of advanced transportation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.577
H-Index - 46
eISSN - 2042-3195
pISSN - 0197-6729
DOI - 10.1002/atr.5670370203
Subject(s) - process (computing) , fuzzy logic , transport engineering , operations research , order (exchange) , computer science , demand forecasting , fuzzy transportation , rail freight transport , fuzzy set , engineering , fuzzy number , economics , artificial intelligence , finance , operating system
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.