Dynamic Prediction Method for Ground Settlement of Reclaimed Airports Based on Grey System Theory

Settlement issues at airports pose a significant threat to operational safety, particularly in coastal regions, where land reclamation introduces unique challenges. The complexities of marine foundations, the difficulties in investigating reclaimed land, and the heightened risks of excessive settlement require timely and accurate monitoring and prediction to effectively identify risks and minimize unnecessary maintenance costs. To address these challenges, this study introduces a dynamic prediction model based on grey system theory, enhanced by a variable-size sliding window mechanism that continuously integrates the latest monitoring data. Validation using datasets from Kansai International Airport and Xiamen Xiang’an International Airport demonstrates that the model improves prediction accuracy by over 20% compared to existing models. Additionally, an exponential forecasting mechanism for long-term settlement prediction is developed and verified with data from Pudong International Airport. The proposed model demonstrates robust predictive capabilities across both long-term and short-term forecasting scenarios.