Recently, Chinese ports container throughput increased rapidly. Accurate forecasting for container throughput of Chinese posts is an important and challengeable problem. We apply an adaptive approach --- Aggregated forecast through exponential reweighting (AFTER), introduced by Yang (2004) to this problem. Two classes of time series models (seasonal ARIMA model and vector autoregressive model) are combined. The results indicated that the AFTER approach has advantage over the common used simply average forecasting, and can automatically put a large weight on the better individual forecast with high frequency.