Ground-motion analysis with Bayes plus AI Expansion
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Bayesian inference is vital for predicting ground motion during earthquakes, addressing inherent uncertainties. It integrates prior knowledge with data, modeling factors like earthquake source, site conditions, and wave paths. Bayesian methods quantify uncertainties and account for spatial correlation of ground motion across regions. They also allow for model updates as new data emerges, refining predictive capabilities. This probabilistic approach moves beyond deterministic predictions, creating more realistic and reliable models for seismic risk assessment, contributing to safer communities.