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This document presents a study on damage state-dependent fragility models for buildings exposed to multiple hazards, specifically earthquakes and floods, using Bayesian modeling and causal inference. The research highlights the importance of prior damage states in predicting structural damage and introduces a novel approach that combines Bayesian inference with causal graphs to enhance model interpretability and accuracy. The findings support applications in disaster risk management and decision-making proc

Author

afifa_41

Language

EN