Seismic vulnerability assessment of low to mid-rise RC buildings addressing prevailing design and construction practices in the Northeastern region of the Indian subcontinent: A case study based approach

Structures ◽  
2021 ◽  
Vol 33 ◽  
pp. 1561-1577
Author(s):  
Sekhar Chandra Dutta ◽  
Lipika Halder ◽  
Richi Prasad Sharma
Keyword(s):  
Vulnerability Assessment ◽  
Seismic Vulnerability ◽  
Indian Subcontinent ◽  
Rc Buildings ◽  
Seismic Vulnerability Assessment ◽  
Northeastern Region ◽  
Design And Construction

scholarly journals Performance of Logistic Regression and Support Vector Machines for Seismic Vulnerability Assessment and Mapping: A Case Study of the 12 September 2016 ML5.8 Gyeongju Earthquake, South Korea

2019 ◽  
Vol 11 (24) ◽  
pp. 7038 ◽  
Author(s):  
Jihye Han ◽  
Soyoung Park ◽  
Seongheon Kim ◽  
Sanghun Son ◽  
Seonghyeok Lee ◽  
...  
Keyword(s):  
Logistic Regression ◽  
South Korea ◽  
Vulnerability Assessment ◽  
Seismic Vulnerability ◽  
Spatial Databases ◽  
Support Vector ◽  
Seismic Vulnerability Assessment ◽  
The Common ◽  
Gyeongju Earthquake

In this study, we performed seismic vulnerability assessment and mapping of the ML5.8 Gyeongju Earthquake in Gyeongju, South Korea, as a case study. We applied logistic regression (LR) and four kernel models based on the support vector machine (SVM) learning method to derive suitable models for assessing seismic vulnerabilities; the results of each model were then mapped and evaluated. Dependent variables were quantified using buildings damaged in the 9.12 Gyeongju Earthquake, and independent variables were constructed and used as spatial databases by selecting 15 sub-indicators related to earthquakes. Success and prediction rates were calculated using receiver operating characteristic (ROC) curves. The success rates of the models (LR, SVM models based on linear, polynomial, radial basis function, and sigmoid kernels) were 0.652, 0.649, 0.842, 0.998, and 0.630, respectively, and the prediction rates were 0.714, 0.651, 0.804, 0.919, and 0.629, respectively. Among the five models, RBF-SVM showed the highest performance. Seismic vulnerability maps were created for each of the five models and were graded as safe, low, moderate, high, or very high. Finally, we examined the distribution of building classes among the 23 administrative districts of Gyeongju. The common vulnerable regions among all five maps were Jungbu-dong and Hwangnam-dong, and the common safe region among all five maps was Gangdong-myeon.

Seismic vulnerability assessment of historical urban centres: case study of the old city centre in Seixal, Portugal

2013 ◽  
Vol 11 (5) ◽  
pp. 1753-1773 ◽  
Author(s):  
Tiago Miguel Ferreira ◽  
Romeu Vicente ◽  
J. A. R. Mendes da Silva ◽  
Humberto Varum ◽  
Aníbal Costa
Keyword(s):  
Vulnerability Assessment ◽  
Seismic Vulnerability ◽  
City Centre ◽  
Seismic Vulnerability Assessment ◽  
Old City
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