The Nonlinear Impact of Demand Expansion Based on Machine Learning on Industrial Upgrading

To explore the effect of demand expansion on industrial upgrading, this study combines theoretical analysis and empirical research, and carries out in-depth analysis of data from 31 provinces in China based on machine learning models. The results showed that the model errors of variables such as Engel coefficient, per capita income growth rate, and high-end consumption were all below 0.02%, indicating that these variables have strong explanatory power for industrial upgrading. The changes in consumer demand have a significant nonlinear impact on the upgrading and rationalization of industrial structure. The expansion of demand positively affects the upgrading of industrial structure, while it negatively affects the rationalization of industrial structure. In summary, the research on the nonlinear impact of demand expansion based on machine learning on industrial upgrading provides support and reference for achieving high-quality industrial development.