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Applying Recurrent Neural Network for Passenger Traffic Forecasting

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Advances in Computer Science for Engineering and Education II (ICCSEEA 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 938))

Abstract

The article represents the analysis of neural networks that can be used to predict passenger traffic between cities. Passenger data nonstationary timetable is considered. A class of recurrent neural networks (RNN) have also been considered, among which the expediency of using the Long Short-Term Memory (LSTM) neural network for analysis and prediction of passenger traffic on the interurban route investigated is selected and substantiated. The stages of the research are represented. The data of the Ukrainian motor transport enterprise for 2007–2015 were used for the experiment. The study uses static methods for predicting the moving average, exponential smoothing of Holt-Winters, linear and logarithmic trends for verification and comparison of forecast accuracy with various methods.

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Author information

Authors and Affiliations

  1. School of Educational Information Technology, Central China Normal University, Wuhan, China

    Zhengbing Hu

  2. National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine

    Ivan Dychka, Liubov Oleshchenko & Sergiy Kukharyev

Authors
  1. Zhengbing Hu
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  2. Ivan Dychka
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  3. Liubov Oleshchenko
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  4. Sergiy Kukharyev
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Corresponding author

Correspondence to Liubov Oleshchenko .

Editor information

Editors and Affiliations

  1. School of Educational Information Technology, Central China Normal University, Wuhan, Hubei, China

    Zhengbing Hu

  2. Mechanical Engineering Research Institute of the Russian Academy of Sciences, Moscow, Russia

    Sergey Petoukhov

  3. “Igor Sikorsky Kiev Polytechnic Institute”, National Technical University of Ukraine, Kiev, Ukraine

    Ivan Dychka

  4. Halmos College of Natural Sciences and Oceanography, Nova Southeastern University, Ft. Lauderdale, FL, USA

    Matthew He

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Hu, Z., Dychka, I., Oleshchenko, L., Kukharyev, S. (2020). Applying Recurrent Neural Network for Passenger Traffic Forecasting. In: Hu, Z., Petoukhov, S., Dychka, I., He, M. (eds) Advances in Computer Science for Engineering and Education II. ICCSEEA 2019. Advances in Intelligent Systems and Computing, vol 938. Springer, Cham. https://doi.org/10.1007/978-3-030-16621-2_7

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