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