A System for Container Terminal Operation Prediction

As water and land transportation hubs, container terminals are important infrastructures for national economic and social development and participation in global competition and cooperation. With the rapid economic development, the container throughput of China's ports is increasing year by year. Accurate prediction of container terminal operation can optimize the terminal resource scheduling and improve the operation efficiency. Therefore, in this paper, we design a system to predict the container terminal operations. Some machine learning and deep learning algorithms are used to predict the number of vessels arriving at the port in the future days and the length of time container barges will be at port. Taking Shanghai Yangshan Port phase IV automated terminal as an example, we also perform some experiments, and the results show that our system can provide accurate predictions for the container terminal operations.