Ground-motion with statistical methods plus AI Expansion
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Statistical methods are crucial for analyzing ground motion during earthquakes, improving seismic hazard assessment. Ground motion models capture variability from earthquake sources, site conditions, and wave paths. Spatial correlation models enhance predictions across regions. Bayesian inference integrates prior knowledge with data, quantifying uncertainties and improving hazard assessments. These statistical tools provide robust predictions, contributing to safer communities by better understanding and predicting earthquake impacts.