Forecasting interregional commodity flows using artificial neural networks: an evaluation
H. Murat Celik
Transportation Planning and Technology, 2004, vol. 27, issue 6, 449-467
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.
Date: 2004
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://hdl.handle.net/10.1080/0308106042000293499 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:transp:v:27:y:2004:i:6:p:449-467
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/GTPT20
DOI: 10.1080/0308106042000293499
Access Statistics for this article
Transportation Planning and Technology is currently edited by Dr. David Gillingwater
More articles in Transportation Planning and Technology from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().