A Study of Logistics Efficiency Prediction in Dalian Port Based on Gray-BP Neural Network

Abstract

The port of Dalian has a long history of development, and the further improvement of its logistics efficiency has important development significance for the hinterland radiation region and China's economy, trade and politics. This paper summarizes the research methods of domestic and foreign scholars on the logistics efficiency of ports in various regions by compiling the annual panel data of Dalian Port from 2008 to 2017. This paper uses the GM (1,1) model to directly predict input indicators, and then fit the relationship between input and output indicators through BP neural network, so as to predict the output data value in 2018-2020, and then compare the logistics efficiency value. Finally, we propose an efficiency improvement strategy and provide an early warning of future developments.