Multipoint Deformation Safety Monitoring Model for Concrete Arch Dams Based on Bayesian Model Selection and Averaging

The deformation properties of concrete arch dams are affected by the synergistic effects multiple factors, featuring strong, multidimensional spatialtemporal evolution and distribution characteristics. This paper proposes a zoned safety monitoring model for dam based on similarity optimization to evaluate state structures. First, clustering points at different locations an was performed using panel data multi-index method determine laws positions dam. Next, multipoint comprehensive displacements each zone were extracted principal component analysis extract uniform law point in zone. Finally, we adopted Bayesian selection (BMS) averaging (BMA) regression set, considering uncertainty model. engineering case study showed that BMA yielded robust effective prediction results mechanism indicated followed general rule. temperature mainly reflected middle with hysteresis effect, time-dependent evident both sides shoulder. proposed this has strong robustness interpretability, which can provide valuable technical support analyzing properties.