CSpace  > 系统科学研究所
Nonlinear vector auto-regression neural network for forecasting air passenger flow
Sun, Shaolong1,2; Lu, Hongxu2; Tsui, Kwok-Leung3; Wang, Shouyang1,2,4
2019-07-01
Source PublicationJOURNAL OF AIR TRANSPORT MANAGEMENT
ISSN0969-6997
Volume78Pages:54-62
AbstractForecasting air passenger flows is receiving increasing attention, especially due to its intrinsic difficulties and wide applications. Total passengers are used as a proxy for air transport demand. However, the time series of air passenger flows usually has complicated behavior with high volatility and irregularity. This paper proposes a MIV-based nonlinear vector auto-regression neural network (NVARNN) approach to forecast air passenger flows. In the proposed MIV-NVARNN learning approach, (1) a method of mean impact value (MIV) based on neural network is used for identifying and extracting input variables; (2) NVARNN is firstly proposed to deal with the irregularity and volatility of the time series of air passenger flows. To illustrate and verify the effectiveness of the proposed approach, we tested its directional and level forecasting accuracy using the time series of Beijing International Airport's passenger flows. The results of out-of-sample forecasting performance show that the proposed MIV-NVARNN approach consistently outperforms single models and other hybrid approaches in terms of level forecasting accuracy, directional forecasting accuracy and robustness analysis.
KeywordAir passenger flow forecasting Nonlinear vector auto-regression Multilayer perceptron neural network Competition over resources algorithm Mean impact value
DOI10.1016/j.jairtraman.2019.04.005
Language英语
Funding ProjectNational Natural Science Foundation of China[71771207] ; National Natural Science Foundation of China[51505307] ; National Natural Science Foundation of China[11471275] ; National Natural Science Foundation of China[71642006] ; General Research Fund[CityU 11216014] ; Research Grants Council of the Hong Kong Special Administrative Region, China[T32-101/15-R]
WOS Research AreaTransportation
WOS SubjectTransportation
WOS IDWOS:000473837500006
PublisherELSEVIER SCI LTD
Citation statistics
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/35159
Collection系统科学研究所
Corresponding AuthorWang, Shouyang
Affiliation1.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Econ & Management, Beijing 100190, Peoples R China
3.City Univ Hong Kong, Sch Data Sci, Kowloon, Tat Chee Ave, Hong Kong, Peoples R China
4.Chinese Acad Sci, Ctr Forecasting Sci, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Sun, Shaolong,Lu, Hongxu,Tsui, Kwok-Leung,et al. Nonlinear vector auto-regression neural network for forecasting air passenger flow[J]. JOURNAL OF AIR TRANSPORT MANAGEMENT,2019,78:54-62.
APA Sun, Shaolong,Lu, Hongxu,Tsui, Kwok-Leung,&Wang, Shouyang.(2019).Nonlinear vector auto-regression neural network for forecasting air passenger flow.JOURNAL OF AIR TRANSPORT MANAGEMENT,78,54-62.
MLA Sun, Shaolong,et al."Nonlinear vector auto-regression neural network for forecasting air passenger flow".JOURNAL OF AIR TRANSPORT MANAGEMENT 78(2019):54-62.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Sun, Shaolong]'s Articles
[Lu, Hongxu]'s Articles
[Tsui, Kwok-Leung]'s Articles
Baidu academic
Similar articles in Baidu academic
[Sun, Shaolong]'s Articles
[Lu, Hongxu]'s Articles
[Tsui, Kwok-Leung]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Sun, Shaolong]'s Articles
[Lu, Hongxu]'s Articles
[Tsui, Kwok-Leung]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.