Basic System Dynamics Theory of Digital Courts Oriented to Social Governance

System dynamics is a modeling and simulation method used to analyze the internal dynamic behavior of complex systems. As a discipline that analyzes the internal mechanisms of a system, it has played an important role in various fields such as economics, environment, and social management in recent years. In order to continuously promote the intelligent construction of courts, optimize relevant systems, and ensure that digital courts better serve social governance, this article will summarize and classify the current digital court business from the perspective of system dynamics model construction, and explore effective ways to enhance the social governance capabilities of digital courts. This paper will focus on three aspects: "social conflict resolution," "improvement of judicial fairness," and "social risk monitoring" to evaluate the capacity enhancement in social governance based on digital court system dynamics mechanisms. It will also provide measures for courts to better understand social dynamics, predict potential risks, and promote social stability and judicial justice under judicial technology empowerment. The theory of imbalanced learning specifically addresses situations where the sample size of certain categories of data is much lower than that of other categories in actual data. Faced with the problem of imbalanced data categories in judicial practice, especially in some complex or special cases where the number is relatively small, its importance for judicial decision-making cannot be ignored. This paper will also describe the path for courts to mine the internal value of imbalanced category case data using artificial intelligence principles by combining imbalanced learning theory with digital court system dynamics mechanisms. Finally, this paper looks forward to the prospects of digital court system dynamics and smart city construction.