Yang, D., 2020. Logistics demand forecast model for port import and export in coastal area. In: Yang, Y.; Mi, C.; Zhao, L., and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 678–681. Coconut Creek (Florida), ISSN 0749-0208.

Port logistics has become one of the main logistics modes. In order to ensure the stability of its development, logistics demand forecasting model is often used to predict port logistics, but the forecasting error is large. Therefore, the coastal port import and export logistics demand forecasting model is designed. This paper analyzes the influencing factors of port import and export logistics demand, obtains the forecast index of port import and export logistics demand, and realizes port import and export logistics demand forecast by using BP neural network. So far, the coastal port import and export logistics demand forecasting model has been constructed. The experimental results show that the error between the prediction results of this model and the actual results is smaller, and the error between the prediction results of the original model and the actual results is larger. Thus, the coastal port import and export logistics demand forecasting model is more accurate, the use of better results.