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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    Titel :

    SVR-Ensemble Forecasting Approach for Ro-Ro Freight at Port of Algeciras (Spain)


    Weitere Titelangaben:

    Advs in Intelligent Syst., Computing


    Beteiligte:
    Graña, Manuel (Herausgeber:in) / López-Guede, José Manuel (Herausgeber:in) / Etxaniz, Oier (Herausgeber:in) / Herrero, Álvaro (Herausgeber:in) / Sáez, José Antonio (Herausgeber:in) / Quintián, Héctor (Herausgeber:in) / Corchado, Emilio (Herausgeber:in) / Moscoso-López, Jose Antonio (Autor:in) / Turias, Ignacio J. (Autor:in) / Aguilar, Juan Jesús Ruiz (Autor:in)

    Kongress:

    The 13th International Conference on Soft Computing Models in Industrial and Environmental Applications ; 2018 ; san sebastian, Spain June 06, 2018 - June 08, 2018



    Erscheinungsdatum :

    07.06.2018


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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