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Short-Term Bus Passenger Demand Prediction Based on Time Series Model and Interactive Multiple Model Approach
Joint Authors
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-04-21
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Although bus passenger demand prediction has attracted increased attention during recent years, limited research has been conducted in the context of short-term passenger demand forecasting.
This paper proposes an interactive multiple model (IMM) filter algorithm-based model to predict short-term passenger demand.
After aggregated in 15 min interval, passenger demand data collected from a busy bus route over four months were used to generate time series.
Considering that passenger demand exhibits various characteristics in different time scales, three time series were developed, named weekly, daily, and 15 min time series.
After the correlation, periodicity, and stationarity analyses, time series models were constructed.
Particularly, the heteroscedasticity of time series was explored to achieve better prediction performance.
Finally, IMM filter algorithm was applied to combine individual forecasting models with dynamically predicted passenger demand for next interval.
Different error indices were adopted for the analyses of individual and hybrid models.
The performance comparison indicates that hybrid model forecasts are superior to individual ones in accuracy.
Findings of this study are of theoretical and practical significance in bus scheduling.
American Psychological Association (APA)
Xue, Rui& Sun, Jian& Chen, Shukai. 2015. Short-Term Bus Passenger Demand Prediction Based on Time Series Model and Interactive Multiple Model Approach. Discrete Dynamics in Nature and Society،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1060728
Modern Language Association (MLA)
Xue, Rui…[et al.]. Short-Term Bus Passenger Demand Prediction Based on Time Series Model and Interactive Multiple Model Approach. Discrete Dynamics in Nature and Society No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1060728
American Medical Association (AMA)
Xue, Rui& Sun, Jian& Chen, Shukai. Short-Term Bus Passenger Demand Prediction Based on Time Series Model and Interactive Multiple Model Approach. Discrete Dynamics in Nature and Society. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1060728
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1060728