SARIMA MODELLING APPROACH FOR RAILWAY PASSENGER FLOW FORECASTING

被引：86

作者：

Milenkovic, Milos ^{[1
]}

Svadlenka, Libor ^{[2
]}

Melichar, Vlastimil ^{[2
]}

Bojovic, Nebojsa ^{[1
]}

Avramovic, Zoran ^{[1
]}

机构：

[1] Univ Belgrade, Fac Transport & Traff Engn, Div Management Railway Rolling Stock & Tract, Belgrade, Serbia

[2] Univ Pardubice, Jan Perner Transport Fac, Dept Transport Management Mkt & Logist, Pardubice, Czech Republic

来源：

TRANSPORT | 2018年 / 33卷 / 05期

关键词：

railway; passenger service; time series; forecasting; SARIMA; VEHICULAR TRAFFIC FLOW; NEURAL-NETWORKS; MOVING AVERAGE; PREDICTION; DEMAND;

D O I：

10.3846/16484142.2016.1139623

中图分类号：

U [交通运输];

学科分类号：

08 ; 0823 ;

摘要：

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.

引用

页码：1113 / 1120

页数：8

共 50 条

[1] SARIMA Modelling Approach for Forecasting of Traffic Accidents
Deretic, Nemanja
Stanimirovic, Dragan
Al Awadh, Mohammed
Vujanovic, Nikola
Djukic, Aleksandar
[J]. SUSTAINABILITY, 2022, 14 (08)
[2] Railway Passenger Flow Forecasting by Integrating Passenger Flow Relationship and Spatiotemporal Similarity
Yu, Song
Luo, Aiping
Wang, Xiang
[J]. INTELLIGENT AUTOMATION AND SOFT COMPUTING, 2023, 37 (02): : 1877 - 1893
[3] Application Of Data Mining In The Forecasting Of Railway Passenger Flow
Zheng, Dan
Wang, Yao
Tang, Pengzhi
Wu, Yanping
[J]. RESEARCH IN MATERIALS AND MANUFACTURING TECHNOLOGIES, PTS 1-3, 2014, 835-836 : 958 - +
[4] Passenger Flow Prediction for Guangzhou-Zhuhai Intercity Railway Based on SARIMA Model
基于SARIMA模型的广珠城际铁路客流量预测
[J]. Peng, Qiyuan (qiyuan-peng@home.swjtu.edu.cn), 1600, Science Press (55):
[5] Passenger Flow Forecasting Research for Airport Terminal Based on SARIMA Time Series Model
Li, Ziyu
Bi, Jun
Li, Zhiyin
[J]. 1ST INTERNATIONAL GLOBAL ON RENEWABLE ENERGY AND DEVELOPMENT (IGRED 2017), 2017, 100
[6] A spatio-temporal forecasting method of railway passenger flow
Xu, W
Huang, HK
Qin, Y
[J]. PROCEEDINGS OF THE 2004 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2004, : 1550 - 1554
[7] Passenger demand forecasting for railway systems
Nar, Melek
Arslankaya, Seher
[J]. OPEN CHEMISTRY, 2022, 20 (01): : 105 - 119
[8] Railway Passenger Flow Forecasting Based on Time Series Analysis with Big Data
Xu, Xiangqian
Dou, Yajie
Zhou, Zhexuan
Liao, Tianjun
Lu, Yanjing
Tan, Yuejin
[J]. PROCEEDINGS OF THE 30TH CHINESE CONTROL AND DECISION CONFERENCE (2018 CCDC), 2018, : 3584 - 3590
[9] An approach for real-time estimation of railway passenger flow
Sugiyama, Yoichi
Matsubara, Hiroshi
Myojo, Shuichi
Tamura, Kazuki
Ozaki, Naoya
[J]. Quarterly Report of RTRI (Railway Technical Research Institute) (Japan), 2010, 51 (02): : 82 - 88
[10] Modelling and Forecasting of Rainfall Time Series Using SARIMA
Dabral P.P.
Murry M.Z.
[J]. Environmental Processes, 2017, 4 (2) : 399 - 419

← 1 2 3 4 5 →