Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/4700
Title: Forecasting interregional commodity flows using artificial neural networks: An evaluation
Authors: Çelik, Hüseyin Murat
Çelik, Hüseyin Murat
Keywords: Freight transportation
Artificial neural networks
Commodity flows
Freight transportation
Spatial interaction models
Issue Date: Dec-2004
Publisher: Taylor and Francis Ltd.
Source: Çelik, H. M. (2004). Forecasting interregional commodity flows using artificial neural networks: An evaluation. Transportation Planning and Technology, 27(6), 449-467. doi:10.1080/0308106042000293499
Abstract: Previous studies have concluded that the use of artificial neural networks (ANNs) is a promising new technique for modelling freight distribution, supporting, the findings of other studies in the area of spatial interaction modelling. However, the forecasting performance of ANNs is still under investigation. This study tests the predictive performance of the ANN Model with respect to a Box-Cox spatial interaction model. It is concluded that the Box-Cox model outperforms ANN in forecasting interregional commodity flows even if ANN had proven calibration superiority in comparison to conventional gravity type models.
URI: http://doi.org/10.1080/0308106042000293499
http://hdl.handle.net/11147/4700
ISSN: 0308-1060
0308-1060
1029-0354
Appears in Collections:Civil Engineering / İnşaat Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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