Regional Import and Export Influencing Factors in Jiangsu Province, China Based on RBF Neural Network Analysis

Abstract

With economic globalization, import and export trade has become a key factor affecting economic growth, and the sample data of Jiangsu province, as an important part of China's import and export trade, is a typical representative. This paper selects the annual data of Jiangsu Province from 2000 to 2021, determines the main influencing factors by rooting in past research theories, adopts the structure, characteristics and training algorithm of RBF (radial basis function) neural network, and applies the neural network to establish a multi-factor nonlinear time series forecasting model based on the mapping relationship between Jiangsu Province's import and export and its influencing factors. The conclusions are as follows: This paper builds a neural network around the data related to the import and export of foreign trade affecting Jiangsu Province from 2000 to 2021, and establishes an indicator system for the trend of foreign trade and the influencing factors of Jiangsu Province. The analysis finds that the highest accuracy is achieved when the neuron is 9. The degree of trade barriers, regional social financing scale, global economic growth rate and financial development efficiency are the main factors influencing the total amount of foreign trade import and export of Jiangsu province. Under the background of global trade being hindered by the epidemic and stagnant, the current situation of foreign trade development in Jiangsu Province should focus on breaking through from the above factors, considering domestic and international economic development, accelerating its financing scale and financial industry development, and promoting the steady development of foreign trade.