A Simulation System for the Evolution of Urbanization Economic Forms Based on Artificial Intelligence Technology

Urbanization has made citizens aware of the importance of the evolution of urban economic forms. This study aims to construct a simulation system based on artificial intelligence technology and historical data to predict the impact of urbanization on urban economic structure. In the first stage of the study, targeted key economic indicators were selected for analysis before and after the implementation of the simulation system. In this study, the Long Short Term Memory (LSTM) model was used to predict the per capita GDP of 11 cities. This article aims to demonstrate the effectiveness of the simulation system in evaluating the impact of urbanization on economic development by comparing the prediction results during different time periods before and after the implementation of artificial intelligence technology. In addition, the time cost before and after the implementation of the simulation system will be compared to further demonstrate the effectiveness of the model. The research results show that after the implementation of the simulation system, the per capita GDP of the city has increased to the highest point of US $16665, while the urban unemployment rate has declined, and the growth rate of fixed assets investment has increased. These changes indicate significant progress in the economic vitality and labor market of cities. This study confirms the application value of artificial intelligence technology in urban economics research, especially in predicting and evaluating the impact of urbanization on economic development. The introduction of LSTM models and the implementation of simulation systems not only improve the accuracy of predictions, but also provide strong data support for urban planning and policy formulation, thereby promoting the healthy development of urban economy.