Path of Regional Economic Transformation and Upgrading Based on Recurrent Neural Network

Abstract

At present, the development of the regional economy is very rapid and widespread. However, due to increasingly prominent problems such as the low level of technological innovation and the unreasonable industrial structure, the economic growth rate has declined. Therefore, it is particularly important to use the circular economy network to study the transformation and upgrading of the regional economy. It clarifies the stakeholders in the process of transformation and upgrading of manufacturing enterprises. Its benefits in the network are given, and symptoms and mobilization methods and the obstacles and solutions to the development of mobilization among various subjects are drawn. In addition, it also emphasizes the equivalence between intelligent products and human subjects in this network. Because of the intelligence carried by products under the current background, diversified connotations and functions are becoming more and more abundant. The empirical results show that the pulling coefficients of residents’ consumption level, the development of modern service industry, and urbanization rate to economic growth are 0.1812, 0.7165, and 0.1635, respectively, while the pulling coefficient of Gini coefficient to economic growth is −0.1785.