Nonparametric binary recursive partitioning for deterioration prediction of infrastructure elements

Li, Z; Pittou, M; Karlaftis, MG

dc.contributor.author	Li, Z	en
dc.contributor.author	Pittou, M	en
dc.contributor.author	Karlaftis, MG	en
dc.date.accessioned	2014-03-01T01:58:46Z
dc.date.available	2014-03-01T01:58:46Z
dc.date.issued	2009	en
dc.identifier.issn	16878086	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/28722
dc.title	Nonparametric binary recursive partitioning for deterioration prediction of infrastructure elements	en
heal.type	journalArticle	en
heal.identifier.primary	10.1155/2009/809767	en
heal.identifier.secondary	809767	en
heal.identifier.secondary	http://dx.doi.org/10.1155/2009/809767	en
heal.publicationDate	2009	en
heal.abstract	This paper introduces binary recursive partitioning (BRP) as a method for estimating bridge deck deterioration and treats it as a classification and decision problem. The proposed BRP method is applied to the Indiana bridge inventory database containing 25 years of detailed information on approximately 5,500 bridges on state-maintained highways. Classification trees are separately created for 4 and 2 prediction classes and relatively high degrees of success are achieved for deck condition prediction. The significant variables identified as the most influential include current deck condition and deck age. The proposed method offers an alternative nonparametric approach for bridge deck condition prediction and could be used for cross comparisons of models calibrated using the widely applied parametric approaches. © 2009 Mariza Pittou et al.	en
heal.journalName	Advances in Civil Engineering	en
dc.identifier.doi	10.1155/2009/809767	en
dc.identifier.volume	2009	en