Application of Artificial Intelligence in Prediction of Road Freight Transportation

  • Bogna Mrowczynska Silesian University of Technology
  • Maria Ciesla Silesian University of Technology
  • Aleksander Krol Silesian University of Technology
  • Aleksander Sladkowski Silesian University of Technology
Keywords: forecasting methods, freight transport, artificial immune system, clonal selection, Bayesian networks, double exponential smoothing,

Abstract

Road freight transport often requires the prediction of volume. Such knowledge is necessary to capture trends in the industry and support decision making by large and small trucking companies. The aim of the presented work is to demonstrate that application of some artificial intelligence methods can improve the accuracy of the forecasts. The first method employed was double exponential smoothing. The modification of this method has been proposed. Not only the parameters but also the initial values were set in order to minimize the mean absolute percentage error (MAPE) using the artificial immune system. This change resulted in a marked improvement in the effects of minimization, and suggests that the variability of the initial value of S2 has an impact on this result. Then, the forecasting Bayesian networks method was applied. The Bayesian network approach is able to take into account not only the historical data concerning the volume of freight, but also the data related to the overall state of the national economy. This significantly improves the quality of forecasting. The application of this approach can also help in predicting the trend changes caused by overall state of economy, which is rather impossible when analysing only the historical data.

Author Biographies

Bogna Mrowczynska, Silesian University of Technology
Faculty of Transport, assoc. prof.
Maria Ciesla, Silesian University of Technology
Faculty of Transport, assoc. prof.
Aleksander Krol, Silesian University of Technology
Faculty of Transport, assoc. prof.
Aleksander Sladkowski, Silesian University of Technology
Faculty of Transport, full prof. and head of Department of Logistics and Industrial Transportation

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Published
2017-08-28
How to Cite
1.
Mrowczynska B, Ciesla M, Krol A, Sladkowski A. Application of Artificial Intelligence in Prediction of Road Freight Transportation. PROMET [Internet]. 2017Aug.28 [cited 2020Jul.4];29(4):363-70. Available from: http://traffic.fpz.hr/index.php/PROMTT/article/view/2227
Section
Articles

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