Regional Collaborative Forecast of Cargo Throughput in China’s Circum-Bohai-Sea Region Based on LSTM Model

Abstract

Any developed port plays a dominant role both in domestic and international trade reflecting economic prosperity of the port and nearby regions in terms of its cargo throughput and port construction. An attempt is made in this study to use long-and short-term memory (LSTM) artificial neural network method to construct the port cargo throughput prediction model. Three ports namely, Tianjin Port, Dalian Port, and Tangshan Port from China’s Bohai Rim region are selected as research objects. The historical cargo throughput of each port for nearly ten years was used as the input index data for joint prediction. The cargo throughput of Bohai Port provides another way to improve the accuracy of port cargo throughput prediction. The prediction results show that the LSTM model can effectively predict the port cargo throughput; the cargo throughput forecasts between the three Bohai Rim ports have both an interactive relationship and differences.