Research on Optimization of Real Estate Regulation Strategy Based on Big Data Analysis

This study is devoted to the optimization of real estate regulation strategy by using big data analysis technology. By gathering and analyzing pertinent real estate market data, utilizing both traditional time series analysis techniques and advanced deep learning models, this paper delves into the relationship between real estate market prices and various factors. It proposes a range of optimization strategies for real estate regulation based on data insights. Our findings demonstrate that economic development levels, land supply, and other factors significantly influence real estate prices. Implementing judicious control measures can effectively mitigate market price fluctuations and foster market stability. The conclusions drawn from this study hold crucial policy implications for government bodies and relevant agencies in crafting effective real estate market regulations. Furthermore, they offer valuable insights and guidance towards achieving a healthy real estate market and sustainable economic growth.