LAUSR

Abstract Seismic risk of buildings is of great concern to public administration, insurance companies and building inhabitants, as well as structural engineers. This study developed a method to estimate seismic risk to unreinforced masonry (URM) buildings based on the use of binary logistic regression on a large database of 543 URM buildings with detailed seismic assessment analysis. The proposed method considers number of stories, type of slab system, vertical irregularities, visual damage, type of masonry material, typical story height and typical plan area as basic estimation variables. These variables have been assigned to some penalty scores depending on the coefficients derived from the binary logistic regression analysis. In total, 443 buildings from the database were used to generate penalty scores, and 100 buildings were reserved for testing of the proposed method. The correct overall estimation rates of the proposed method for the database (443 buildings) and the test database (100 buildings) were determined as approximately 95% and 86%, respectively.