Journal of East China Normal University(Natural Science) >

2015 , Vol. 2015 >Issue 1: 234 - 239

DOI: https://doi.org/10.3969/j.issn.10005641.2015.01.028

Article

Forecasting of Shanghai Port container throughput  under seasonal variation influence

  • DU Gang ,
  • LIU Ya-Nan
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  • Business School, East China Normal University, Shanghai 200241, China

Received date: 2014-11-01

  Online published: 2015-03-29

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Abstract

It is very important for successful port operation and effective decisionmakingby forecasting container throughput accurately. The Autoregressive Integrated Moving Average model (ARIMA) and the Seasonal Autoregressive Integrated Moving Average model(SARIMA) are applied to the monthly data from 2007 to 2012 of Shanghai Port container throughput to forecast the container throughput of Shanghai Port. The seasonal variation of monthly port container throughputdata can be handled by SARIMA. Compared with ARIMA, SARIMA performed better and improved the Port container throughputprediction accuracy because of removing the seasonal variation.

Key words： Autoregressive Integrated Moving Average model (ARIMA); Seasonal Autoregressive Integrated Moving Average model (SARIMA); port container; throughput;; forecasting

Cite this article

DU Gang , LIU Ya-Nan . Forecasting of Shanghai Port container throughput  under seasonal variation influence[J]. Journal of East China Normal University(Natural Science), 2015 , 2015(1) : 234 -239 . DOI: 10.3969/j.issn.10005641.2015.01.028

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