Article ID Journal Published Year Pages File Type
495921 Applied Soft Computing 2013 10 Pages PDF
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.

Graphical abstractFigure optionsDownload full-size imageDownload as PowerPoint slideHighlights► We propose three hybrid approaches for container throughput forecasting. ► They can achieve better forecasting performance than individual models. ► Seasonal nature and nonlinear characteristic of time series should be captured. ► The “divide and conquer” principle is efficient.

Related Topics
Physical Sciences and Engineering Computer Science Computer Science Applications
Authors
, , , ,