气候变化领域集成服务门户(CCPortal): Prediction of potential seismic damage using classification and regression trees: a case study on earthquake damage databases from Turkey

CCPortal

DOI	10.1007/s11069-020-04125-2
	Prediction of potential seismic damage using classification and regression trees: a case study on earthquake damage databases from Turkey
	Yerlikaya-Özkurt F.; Askan A.
发表日期	2020
ISSN	0921030X
起始页码	3163
结束页码	3180
卷号	103 期号:3
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.
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
语种	英语
来源期刊	Natural Hazards
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/206028
作者单位	Department of Industrial Engineering, Atılım University, Ankara, 06830, Turkey; Department of Civil Engineering, Middle East Technical University, Ankara, 06800, Turkey
推荐引用方式 GB/T 7714	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],2020,103(3).
APA	Yerlikaya-Özkurt F.,&Askan A..(2020).Prediction of potential seismic damage using classification and regression trees: a case study on earthquake damage databases from Turkey.Natural Hazards,103(3).
MLA	Yerlikaya-Özkurt F.,et al."Prediction of potential seismic damage using classification and regression trees: a case study on earthquake damage databases from Turkey".Natural Hazards 103.3(2020).