Empirical analysis of spatial structure of digital economy in green port coupling places based on panel data analysis and mining

This study integrates IoT and deep learning to develop a comprehensive framework for Green Port development aimed at promoting sustainable logistics that supports regional economic growth in coastal and inland areas of China. Using spatial econometrics and panel data analysis, the research investigatexs the complex coupling between logistics and economic subsystems, highlighting spatial heterogeneity and the significant influence of local economic factors. The study employs a three-dimensional spatial model to examine the evolving dynamics of logistics and business flows. At the same time, an evaluation index system is constructed to assess the coordination of Green Port subsystems. ARIMA-BP predictive modelling for the 2020–2025 period suggests a trend towards improved coupling and coordination across most regions, providing strategic insights for sustainable logistics investments and regional integration. This work contributes to the understanding of Green Port logistics development and offers policy recommendations for regional economic alignment.