Research on the Integration of Artificial Intelligence-driven Industrial Economics and Technology Industry Incubation

Abstract

The development mode relying on the traditional factor dividend has become unsustainable, and the integration and application of artificial intelligence technology can promote the high-quality development of science and technology industry incubation, and it brings more space for the development of the science and technology industry economy. This paper firstly discusses how artificial intelligence predicts economic trends, optimizes the production process, and automates decision support systems through machine learning models. By analyzing how AI processes large amounts of economic data, identifying market patterns, and evaluating the value of investment projects in future markets, it is able to assess the value of investment projects in future markets. Aiming at the shortcomings of the original K-Means clustering algorithm, the method of determining the initial clustering center and the method of automatically determining the K-value are investigated so as to realize the automatic clustering of industrial economic development data. From the empirical analysis, it can be seen that the regression coefficients of the interaction term Treatit × Yearit in columns (1) and (2) are all significantly positive at the 1% level. The cluster analysis also visualizes both the types and levels of enterprises in the economic development in a more intuitive way, which shows that the AI model can drive the development of the industrial economy and has an irreplaceable position in the process of technology industry incubation.

Keywords

• k-means clustering
• industrial economy
• science and technology industry
• regression coefficient
• 97m50