Abstract
The forecasting of the freight transportation provides a helpful information in the management of ports environment and can be used as a decision-making tool. This work addresses the forecasting of ro-ro (roll-on roll-off) freight flow in a port using a two-stage approach by an ensemble of the best Support Vector Regression (SVR) models. The time series used for forecasting is daily ro-ro freight in the port of Algeciras during the period from 2000 to 2007. Additionally, the time series was preprocessed through an exponential smoothing in order to improve the performance. The experiment results show that the proposed approach is a promising tool in freight forecasting.
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Acknowledgments
This work is part of the coordinated research projects TIN2014-58516-C2-1-R and TIN2014-58516-C2-2-R supported by (MICINN Ministerio de Economía y Competi-tividad-Spain). The data have been kindly provided by Port Authority of Algeciras Bay.
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Moscoso-López, J.A., Turias, I.J., Aguilar, J.J.R., Gonzalez-Enrique, F.J. (2019). SVR-Ensemble Forecasting Approach for Ro-Ro Freight at Port of Algeciras (Spain). In: Graña, M., et al. International Joint Conference SOCO’18-CISIS’18-ICEUTE’18. SOCO’18-CISIS’18-ICEUTE’18 2018. Advances in Intelligent Systems and Computing, vol 771. Springer, Cham. https://doi.org/10.1007/978-3-319-94120-2_34
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