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Forecasting container throughput based on wavelet transforms within a decomposition-ensemble methodology: a case study of China
Xie, Gang1; Qian, Yatong1,2; Yang, Hewei1
2019-02-17
Source PublicationMARITIME POLICY & MANAGEMENT
ISSN0308-8839
Volume46Issue:2Pages:178-200
AbstractTo improve predictive accuracy, new hybrid models are proposed for container throughput forecasting based on wavelet transforms and data characteristic analysis (DCA) within a decomposition-ensemble methodology. Because of the complexity and nonlinearity of the time series of container throughputs at ports, the methodology decomposes the original time series into several components, which are rather simpler sub-sequences. Consequently, difficult forecasting tasks are simplified into a number of relatively easier subtasks. In this way, the proposed hybrid models can improve the accuracy of forecasting significantly. In the methodology, four main steps are involved: data decomposition, component reconstruction based on the DCA, individual prediction for each reconstructed component, and ensemble prediction as the final output. An empirical analysis was conducted for illustration and verification purposes by using time series of container throughputs at three main ports in Bohai Rim, China. The results suggest that the proposed hybrid models are able to forecast better than do other benchmark models. Forecasting may facilitate effective real-time decision making for strategic management and policy drafting. Predictions of container throughput can help port managers make tactical and operational decisions, such as operations planning in ports, the scheduling of port equipment, and route optimization.
KeywordContainer throughput wavelet transform data characteristic analysis time series forecasting decomposition-ensemble methodology
DOI10.1080/03088839.2018.1476741
Language英语
Funding ProjectNational Natural Science Foundation of China[71771207] ; National Natural Science Foundation of China[71372176] ; National Natural Science Foundation of China[71390331] ; National Center for Mathematics and Interdisciplinary Sciences, CAS
WOS Research AreaTransportation
WOS SubjectTransportation
WOS IDWOS:000453701300003
PublisherROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
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Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/31851
Collection系统科学研究所
Affiliation1.Chinese Acad Sci, Acad Math & Syst Sci, MDIS, CFS, Beijing, Peoples R China
2.Univ Chinese Acad Sci, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Xie, Gang,Qian, Yatong,Yang, Hewei. Forecasting container throughput based on wavelet transforms within a decomposition-ensemble methodology: a case study of China[J]. MARITIME POLICY & MANAGEMENT,2019,46(2):178-200.
APA Xie, Gang,Qian, Yatong,&Yang, Hewei.(2019).Forecasting container throughput based on wavelet transforms within a decomposition-ensemble methodology: a case study of China.MARITIME POLICY & MANAGEMENT,46(2),178-200.
MLA Xie, Gang,et al."Forecasting container throughput based on wavelet transforms within a decomposition-ensemble methodology: a case study of China".MARITIME POLICY & MANAGEMENT 46.2(2019):178-200.
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