DOI: 10.1007/s11069-020-04125-2
论文题名: Prediction of potential seismic damage using classification and regression trees: a case study on earthquake damage databases from Turkey
作者: Yerlikaya-Özkurt F. ; Askan A.
刊名: Natural Hazards
ISSN: 0921030X
出版年: 2020
卷: 103, 期: 3 起始页码: 3163
结束页码: 3180
语种: 英语
中文关键词: Classification and regression tree
; Damage prediction
; Earthquakes
; Seismic damage
英文关键词: classification
; database
; earthquake damage
; earthquake prediction
; performance assessment
; regression analysis
; reinforced concrete
; structural analysis
; Turkey
英文摘要: Seismic damage estimation is an important key ingredient of seismic loss modeling, risk mitigation and disaster management. It is a problem involving inherent uncertainties and complexities. Thus, it is important to employ robust approaches which will handle the problem accurately. In this study, classification and regression tree approach is applied on damage data sets collected from reinforced concrete frame buildings after major previous earthquakes in Turkey. Four damage states ranging from None to Severe are used, while five structural parameters are employed as damage identifiers. For validation, results of classification analyses are compared against observed damage states. Results in terms of well-known classification performance measures indicate that when the size of the database is larger, the correct classification rates are higher. Performance measures computed for Test data set indicate similar success to that of Train data set. The approach is found to be effective in classifying randomly selected damage data. © 2020, Springer Nature B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/168827
Appears in Collections: 气候变化与战略
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作者单位: Department of Industrial Engineering, Atılım University, Ankara, 06830, Turkey; Department of Civil Engineering, Middle East Technical University, Ankara, 06800, Turkey
Recommended Citation:
Yerlikaya-Özkurt F.,Askan A.. Prediction of potential seismic damage using classification and regression trees: a case study on earthquake damage databases from Turkey[J]. Natural Hazards,2020-01-01,103(3)