Application of Artificial Neural Networks and Singular-Spectral Analysis in Forecasting the Daily Traffic in the Moscow Metro
1 Joint Institute for Nuclear Research (JINR), Dubna, Moscow region, Russia
2 National Research Nuclear University “MEPhI”, Moscow, Russia
3 Federal Treasury Institution “Rostransmodernizatsia”, Moscow, Russia
Published online: 14 February 2018
In this paper, we investigate the possibility of applying various approaches to solving the problem of medium-term forecasting of daily passenger traffic volumes in the Moscow metro (MM): 1) on the basis of artificial neural networks (ANN); 2) using the singular-spectral analysis implemented in the package “Caterpillar”-SSA; 3) sharing the ANN and the “Caterpillar”-SSA approach. We demonstrate that the developed methods and algorithms allow us to conduct medium-term forecasting of passenger traffic in the MM with reasonable accuracy.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).