Research on Early Warning Mechanism of High-Speed Railway Subgrade Settlement based on Artificial Neural Network

China's railway industry, particularly the high-speed railway sector, has experienced remarkable advancements and rapid growth. However, in the vicinity of new railway projects where high-speed railways are operational, it is crucial to assess the potential impacts of additional settlement and deformation on the existing infrastructure during the design phase. Furthermore, effective measures must be implemented during both the design and construction stages. This paper proposes the utilization of Artificial Neural Network (ANN) to address the challenges associated with subgrade settlement prevention. To overcome the issues of subgrade settlement and deformation control in high-speed railways, there is a need for innovative, lightweight, and high-strength subgrade structures and materials. By continuously enhancing the model's modules, the functionality of the model is strengthened. The research presented in this paper focuses on the in-depth exploration of ANN to develop novel subgrade structures and materials that can effectively mitigate high-speed railway subgrade settlement and deformation challenges.