Intelligent Modelling with Alternative Approach: Application of Advanced Artificial Intelligence into Traffic Management

  • Viliam Lendel
  • Lucia Pancikova
  • Lukas Falat
  • Dusan Marcek
Keywords: forecasting, artificial intelligence, intelligent transport system, machine learning, support vector machines, upport vector regression, R software, statistical methods

Abstract

The currently existing transport infrastructures are failing due to many problems. This paper deals with presenting a new approach of modelling and forecasting transport processes using artificial intelligence. Firstly, the current state of forecasting transport data is presented; the traditional as well as new artificial intelligence methods, such as artificial neural networks, are discussed and described. After that, a support vector regression prediction model is briefly presented and an empirical analysis is performed. Finally, on the basis of our experiment and performed comparative analysis we state that artificial intelligence (AI) intelligent methods have potential in the transport area as they can improve the efficiency, safety, and environmental compatibility of transport systems

Author Biographies

Viliam Lendel

Department of Management Theories, Faculty of Management Science and Informatics, University of Zilina, Slovakia

Lucia Pancikova

Department of Macro and Microeconomics, Faculty of Management Science and Informatics, University of Zilina, Slovakia

Lukas Falat

Department of Macro and Microeconomics, Faculty of Management Science and Informatics, University of Zilina, Slovakia

Dusan Marcek

Research Institute of the IT4Innovations Centre of Excellence, Silesian University in Opava, Czech Republic

Published
2017-12-31
How to Cite
Lendel, V., Pancikova, L., Falat, L., & Marcek, D. (2017). Intelligent Modelling with Alternative Approach: Application of Advanced Artificial Intelligence into Traffic Management. Communications - Scientific Letters of the University of Zilina, 19(4), 36-42. Retrieved from http://journals.uniza.sk/index.php/communications/article/view/268
Section
Articles