Forecasting daily passenger traffic volumes in the Moscow metro
Abstract
In this paper we have developed a methodology for the medium-term prediction of daily volumes of passenger traffic in the Moscow metro. It includes three options for the forecast: (1) based on artificial neural networks (ANNs), (2) singular-spectral analysis implemented in the Caterpillar-SSA package, and (3) a combination of the ANN and Caterpillar-SSA approaches. The methods and algorithms allow the mediumterm forecasting of passenger traffic flows in the Moscow metro with reasonable accuracy.
- Publication:
-
Physics of Particles and Nuclei Letters
- Pub Date:
- January 2018
- DOI:
- 10.1134/S1547477118010089
- Bibcode:
- 2018PPNL...15..107I