The forecast of a container traffic has been very important for port plan and development. Generally, Statistic methods, such as moving average method, exponential smoothing, regression analysis, have been much used for traffic forecasting. But, by considering various factors related to the port affect the forecasting of container volume, neural network of parallel processing system can be effective to forecast container volume based on various factors.