Nonlinear vector auto-regression neural network for forecasting air passenger flow

doi:10.1016/j.jairtraman.2019.04.005

CSpace > 系统科学研究所

	Nonlinear vector auto-regression neural network for forecasting air passenger flow
	Sun, Shaolong 1,2; Lu, Hongxu 2; Tsui, Kwok-Leung 3; Wang, Shouyang1,2,4
	2019-07-01
发表期刊	JOURNAL OF AIR TRANSPORT MANAGEMENT
ISSN	0969-6997
卷号	78 页码:54-62
摘要	Forecasting 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.
关键词	Air passenger flow forecasting Nonlinear vector auto-regression Multilayer perceptron neural network Competition over resources algorithm Mean impact value
DOI	10.1016/j.jairtraman.2019.04.005
语种	英语
资助项目	National 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研究方向	Transportation
WOS类目	Transportation
WOS记录号	WOS:000473837500006
出版者	ELSEVIER SCI LTD
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/35159
专题	系统科学研究所
通讯作者	Wang, Shouyang
作者单位	1.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
推荐引用方式 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.