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Hybrid approaches based on LSSVR model for container throughput forecasting: A comparative study.

Authors :
Xie, Gang
Wang, Shouyang
Zhao, Yingxue
Lai, Kin Keung
Source :
Applied Soft Computing; May2013, Vol. 13 Issue 5, p2232-2241, 10p
Publication Year :
2013

Abstract

Abstract: In this study, three hybrid approaches based on least squares support vector regression (LSSVR) model for container throughput forecasting at ports are proposed. The proposed hybrid approaches are compared empirically with each other and with other benchmark methods in terms of measurement criteria on the forecasting performance. The results suggest that the proposed hybrid approaches can achieve better forecasting performance than individual approaches. It is implied that the description of the seasonal nature and nonlinear characteristics of container throughput series is important for good forecasting performance, which can be realized efficiently by decomposition and the “divide and conquer” principle. [Copyright &y& Elsevier]

Details

Language :
English
ISSN :
15684946
Volume :
13
Issue :
5
Database :
Supplemental Index
Journal :
Applied Soft Computing
Publication Type :
Academic Journal
Accession number :
86418120
Full Text :
https://doi.org/10.1016/j.asoc.2013.02.002