Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7428003 | Transportation Research Part E: Logistics and Transportation Review | 2017 | 19 Pages |
Abstract
In this study, a novel decomposition-ensemble methodology is proposed for container throughput forecasting. Firstly, the sample data of container throughput at ports are decomposed into several components. Secondly, the time series of the various components are thoroughly investigated to accurately capture the data characteristics. Then, an individual forecasting model is selected for each component based on the data characteristic analysis (DCA). Finally, the forecasting results are combined as an aggregated output. An empirical analysis is implemented for illustration and verification purposes. Our results suggest that proposed hybrid models can achieve better performance than other methods.
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Authors
Gang Xie, Ning Zhang, Shouyang Wang,