季节性变动影响下的上海港集装箱吞吐量预测

港口吞吐量精准预测对于每一个港口的成功经营和有效决策都十分重要.季节性波动经常会影响港口吞吐量,为了更为准确地预测上海港口集装箱吞吐量,本文选取2007年至2012年上海港母港集装箱吞吐量的月度数据,并对于港口集装箱吞吐量的月度数据中出现的季节性波动进行了处理,采用季节时间序列模型对其进行预测.为了说明方法的有效性,以同样的数据,使用整自回归移动平均模型对上海港集装箱吞吐量进行预测.两种方法预测结果进行对比发现,利用季节时间序列模型对港口集装箱吞吐量季节性进行处理,能够提高港口集装箱吞吐量的预测精度.

Forecasting of Shanghai Port container throughput under seasonal variation influence

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.