Research on the Construction and Application of AI-Based Failure Prediction Model for Rail Transportation Equipment - Lin, Tao (International Journal of Computer Science and Information Technology, 2025)
In order to improve the intelligent operation and maintenance level of rail transit systems in smart cities, the application of artificial intelligence (AI)-based fault prediction models in rail transit equipment maintenance is studied. A fault prediction model with strong predictive ability and adaptability is constructed by fusing multi-source data, including equipment operation status, environmental factors and city dynamic information. The results show that the model has significant advantages in reducing operation interruptions, lowering maintenance costs, optimizing resource scheduling, and improving the reliability and efficiency of rail transit systems. Through multi-system collaboration and intelligent operation and maintenance, the model helps to promote the intelligent upgrading of rail transit and improve the response speed and service quality of urban transportation systems.