It is very important for successful port operation and effective decisionmakingby 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.
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.10005641.2015.01.028
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