Bayesian Belief Network model data sets for seismic damage assessment of masonry buildings

This repository provides the datasets used to develop and validate a Bayesian Belief Network (BBN) model for seismic damage assessment of masonry buildings. The "Training_Database.xlsx" file contains observed data from post-earthquake surveys, including building characteristics, vulnerability parameters, seismic intensity measures, and corresponding damage levels, used to train the BBN model. The "Testing_Database.xlsx" file includes an independent dataset with the same variables, employed to evaluate the predictive performance and generalization capability of the model. The "Conditional_Probability_Tables.xlsx" file reports the conditional probability tables defining the probabilistic dependencies among variables in the BBN, enabling damage state inference under different seismic scenarios. These datasets support reproducibility and further research in probabilistic seismic risk assessment at both building and territorial scales.