Seaport container throughputs are utmost essential indicator for a successful container terminal as it could impact the utilization of resources for terminal operation. The accuracy of throughput forecasting would enable for potential of terminal growth in future. The paper aims to achieve efficient forecasting models by incorporating data throughputs from 2007 to 2015 from the Marine Department of Malaysia. This research focuses on the original ARIMA and the modified model SARIMA for a better model. The forecast results of container throughputs achieved from 2016 to 2018 are then compared with actual figures and then discussed.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    The Analysis of Container Terminal Throughput Using ARIMA and SARIMA


    Weitere Titelangaben:

    Adv Struct Mater


    Beteiligte:
    Ismail, Azman (Herausgeber:in) / Dahalan, Wardiah Mohd (Herausgeber:in) / Öchsner, Andreas (Herausgeber:in) / Mokhtar, Kasypi (Autor:in) / Mhd Ruslan, Siti Marsila (Autor:in) / Abu Bakar, Anuar (Autor:in) / Jeevan, Jagan (Autor:in) / Othman, Mohd Rosni (Autor:in)

    Erschienen in:

    Design in Maritime Engineering ; Kapitel : 18 ; 229-243


    Erscheinungsdatum :

    2022-02-15


    Format / Umfang :

    15 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Forecasting COVID-19 impact on RWI/ISL container throughput index by using SARIMA models

    Koyuncu, Kaan / Tavacioğlu, Leyla / Gökmen, Neslihan et al. | Taylor & Francis Verlag | 2021


    Multivariate Traffic Forecasting Technique Using Cell Transmission Model and SARIMA Model

    Szeto, W.Y. / Ghosh, B. / Basu, B. et al. | British Library Online Contents | 2009


    SARIMA MODELLING APPROACH FOR RAILWAY PASSENGER FLOW FORECASTING

    Miloš Milenković / Libor Švadlenka / Vlastimil Melichar et al. | DOAJ | 2018

    Freier Zugriff


    SARIMA damp trend grey forecasting model for airline industry

    Carmona-Benítez, Rafael Bernardo / Nieto, María Rosa | Elsevier | 2020