SARIMA MODELLING APPROACH FOR RAILWAY PASSENGER FLOW FORECASTING

SARIMA MODELLING APPROACH FOR RAILWAY PASSENGER FLOW FORECASTING

In this paper, railway passenger flows are analyzed and a suitable modeling method proposed. Based on historical data composed from monthly passenger counts realized on Serbian railway network it is concluded that the time series has a strong autocorrelation of seasonal characteristics. In order to...

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Main Authors: Miloš Milenković, Libor Švadlenka, Vlastimil Melichar, Nebojša Bojović, Zoran Avramović
Format: Article
Language:English
Published: Vilnius Gediminas Technical University 2018-12-01
Series:Transport
Subjects:
railway
passenger service
time series
forecasting
SARIMA
Online Access:https://doi.org/10.3846/16484142.2016.1139623
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spelling doaj-a6fa3454605742b2aabf23014739a0ad2021-07-02T07:12:49ZengVilnius Gediminas Technical UniversityTransport1648-41421648-34802018-12-013351113112010.3846/16484142.2016.1139623SARIMA MODELLING APPROACH FOR RAILWAY PASSENGER FLOW FORECASTINGMiloš Milenković0Libor Švadlenka1Vlastimil Melichar2Nebojša Bojović3Zoran Avramović4University of BelgradeUniversity of PardubiceUniversity of PardubiceUniversity of BelgradeUniversity of BelgradeIn this paper, railway passenger flows are analyzed and a suitable modeling method proposed. Based on historical data composed from monthly passenger counts realized on Serbian railway network it is concluded that the time series has a strong autocorrelation of seasonal characteristics. In order to deal with seasonal periodicity, Seasonal AutoRegressive Integrated Moving Average (SARIMA) method is applied for fitting and forecasting the time series that spans over the January 2004 – June 2014 periods. Experimental results show good prediction performances. Therefore, developed SARIMA model can be considered for forecasting of monthly passenger flows on Serbian railways.https://doi.org/10.3846/16484142.2016.1139623railwaypassenger servicetime seriesforecastingSARIMA
collection DOAJ
language English
format Article
sources DOAJ
author Miloš Milenković
Libor Švadlenka
Vlastimil Melichar
Nebojša Bojović
Zoran Avramović
spellingShingle Miloš Milenković
Libor Švadlenka
Vlastimil Melichar
Nebojša Bojović
Zoran Avramović
SARIMA MODELLING APPROACH FOR RAILWAY PASSENGER FLOW FORECASTING
Transport
railway
passenger service
time series
forecasting
SARIMA
author_facet Miloš Milenković
Libor Švadlenka
Vlastimil Melichar
Nebojša Bojović
Zoran Avramović
author_sort Miloš Milenković
title SARIMA MODELLING APPROACH FOR RAILWAY PASSENGER FLOW FORECASTING
title_short SARIMA MODELLING APPROACH FOR RAILWAY PASSENGER FLOW FORECASTING
title_full SARIMA MODELLING APPROACH FOR RAILWAY PASSENGER FLOW FORECASTING
title_fullStr SARIMA MODELLING APPROACH FOR RAILWAY PASSENGER FLOW FORECASTING
title_full_unstemmed SARIMA MODELLING APPROACH FOR RAILWAY PASSENGER FLOW FORECASTING
title_sort sarima modelling approach for railway passenger flow forecasting
publisher Vilnius Gediminas Technical University
series Transport
issn 1648-4142
1648-3480
publishDate 2018-12-01
description In this paper, railway passenger flows are analyzed and a suitable modeling method proposed. Based on historical data composed from monthly passenger counts realized on Serbian railway network it is concluded that the time series has a strong autocorrelation of seasonal characteristics. In order to deal with seasonal periodicity, Seasonal AutoRegressive Integrated Moving Average (SARIMA) method is applied for fitting and forecasting the time series that spans over the January 2004 – June 2014 periods. Experimental results show good prediction performances. Therefore, developed SARIMA model can be considered for forecasting of monthly passenger flows on Serbian railways.
topic railway
passenger service
time series
forecasting
SARIMA
url https://doi.org/10.3846/16484142.2016.1139623
work_keys_str_mv AT milosmilenkovic sarimamodellingapproachforrailwaypassengerflowforecasting
AT liborsvadlenka sarimamodellingapproachforrailwaypassengerflowforecasting
AT vlastimilmelichar sarimamodellingapproachforrailwaypassengerflowforecasting
AT nebojsabojovic sarimamodellingapproachforrailwaypassengerflowforecasting
AT zoranavramovic sarimamodellingapproachforrailwaypassengerflowforecasting
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