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- W2231844124 abstract "Existing empirical fragility assessment methodologies are based on the assumption that damage data are highly reliable. However, these methods are incapable of constructing reliable fragility curves using databases contaminated with sizeable misclassification errors. These databases occur from rapid field surveys undertaken by often inexperienced engineers or, recently, due to the use of remote sensing techniques, either based on satellite, aerial or street view images. The aim of this study is to relax the assumption of high quality data and, thus, construct reliable fragility curves using databases contaminated with misclassification errors through a Bayesian ordinal regression analysis method. The proposed method is applied on the damage data collected from the first round of safety assessment of 30,783 masonry residential buildings affected by the 1978 Thessaloniki earthquake. The comparison of the proposed method with a simpler model which ignores the misclassification error highlighted the potentially significant contribution of the misclassification error in the mean fragility curves as well as their posterior uncertainty intervals. © 2013 Taylor & Francis Group, London." @default.
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- W2231844124 date "2014-01-09" @default.
- W2231844124 modified "2023-09-26" @default.
- W2231844124 title "Sensitivity of empirical fragility assessment of buildings to the misclassification error of damage" @default.
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- W2231844124 doi "https://doi.org/10.1201/b16387-131" @default.
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