Research on Cross-domain Data Flow Based on Intelligent Decision-making Algorithms

As network environments become increasingly complex, cross-domain transfer systems play a crucial role in modern communication and data transmission. Intelligently selecting the optimal path among multiple links, such as VPN and satellite communications, has become a key challenge for enhancing system performance. This paper proposes an intelligent routing method based on parameter weighting and data-driven weight optimization, combined with machine learning algorithms like Decision Trees, to achieve adaptive optimization of link selection. Through theoretical derivation and experimental analysis, the results demonstrate that this method can effectively improve the accuracy and robustness of routing decisions, providing a theoretical foundation and methodological support for the efficient operation of cross-domain transfer systems.