Forecasting interregional commodity flows using artificial neural networks: an evaluation

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.