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Advanced Predictive Methods of Artificial Intelligence in Intelligent Transport Systems

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9714))

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Abstract

Today, more and more, researchers have been trying to apply artificial intelligence (AI) into the area of transport. Using these methods, they try to solve difficult and complex transport problems and improve the efficiency, safety, and environmental-compatibility of transport systems. The main goal of this paper is to present how artificial intelligence can be applied in the area of traffic and transport with less time and money. The paper itself deals with the application of artificial intelligence method (i.e. support vector regression) for time series forecasting in terms of intelligent transport systems.

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Acknowledgments

This paper was partially supported by the Slovak scientific grant VEGA 1/0942/14 Dynamic modelling and soft techniques in predicting economic variables and the Slovak scientific grant VEGA 1/0363/14 Innovation management – processes, strategy and performance.

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Authors and Affiliations

  1. Faculty of Management Science and Informatics, University of Zilina, Univerzitna 8215/1, 010 26, Zilina, Slovakia

    Viliam Lendel, Lucia Pancikova & Lukas Falat

Authors
  1. Viliam Lendel
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  2. Lucia Pancikova
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  3. Lukas Falat
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Corresponding author

Correspondence to Viliam Lendel .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Xi'an Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

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Lendel, V., Pancikova, L., Falat, L. (2016). Advanced Predictive Methods of Artificial Intelligence in Intelligent Transport Systems. In: Tan, Y., Shi, Y. (eds) Data Mining and Big Data. DMBD 2016. Lecture Notes in Computer Science(), vol 9714. Springer, Cham. https://doi.org/10.1007/978-3-319-40973-3_16

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  • DOI: https://doi.org/10.1007/978-3-319-40973-3_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40972-6

  • Online ISBN: 978-3-319-40973-3

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