Fuzzy Temporal Logic Based Railway Passenger Flow Forecast Model
Joint Authors
Jia, Li-min
Wang, Li
Xu, Jie
Huang, Yakun
Dou, Fei
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-11-05
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Passenger flow forecast is of essential importance to the organization of railway transportation and is one of the most important basics for the decision-making on transportation pattern and train operation planning.
Passenger flow of high-speed railway features the quasi-periodic variations in a short time and complex nonlinear fluctuation because of existence of many influencing factors.
In this study, a fuzzy temporal logic based passenger flow forecast model (FTLPFFM) is presented based on fuzzy logic relationship recognition techniques that predicts the short-term passenger flow for high-speed railway, and the forecast accuracy is also significantly improved.
An applied case that uses the real-world data illustrates the precision and accuracy of FTLPFFM.
For this applied case, the proposed model performs better than the k-nearest neighbor (KNN) and autoregressive integrated moving average (ARIMA) models.
American Psychological Association (APA)
Dou, Fei& Jia, Li-min& Wang, Li& Xu, Jie& Huang, Yakun. 2014. Fuzzy Temporal Logic Based Railway Passenger Flow Forecast Model. Computational Intelligence and Neuroscience،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1034659
Modern Language Association (MLA)
Dou, Fei…[et al.]. Fuzzy Temporal Logic Based Railway Passenger Flow Forecast Model. Computational Intelligence and Neuroscience No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-1034659
American Medical Association (AMA)
Dou, Fei& Jia, Li-min& Wang, Li& Xu, Jie& Huang, Yakun. Fuzzy Temporal Logic Based Railway Passenger Flow Forecast Model. Computational Intelligence and Neuroscience. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1034659
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1034659