Investigating pavement cracking: Evolutionary modular neural network approach

Loizos, A; Karlaftis, A

dc.contributor.author	Loizos, A	en
dc.contributor.author	Karlaftis, A	en
dc.date.accessioned	2014-03-01T02:44:05Z
dc.date.available	2014-03-01T02:44:05Z
dc.date.issued	2006	en
dc.identifier.issn	03611981	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31660
dc.subject	Modular Neural Network	en
dc.subject.other	Evolutionary modular neural network	en
dc.subject.other	Pavement cracking	en
dc.subject.other	Pavement distress	en
dc.subject.other	Pavement performance modeling	en
dc.subject.other	Classification (of information)	en
dc.subject.other	Data reduction	en
dc.subject.other	Mathematical models	en
dc.subject.other	Modular construction	en
dc.subject.other	Neural networks	en
dc.subject.other	Pavements	en
dc.subject.other	Crack initiation	en
dc.title	Investigating pavement cracking: Evolutionary modular neural network approach	en
heal.type	conferenceItem	en
heal.identifier.primary	10.3141/1970-24	en
heal.identifier.secondary	http://dx.doi.org/10.3141/1970-24	en
heal.publicationDate	2006	en
heal.abstract	Because of the combined practical and theoretical interest in pavement performance modeling, much research has concentrated on this area during the past few years. The objectives of this study are, first, to cluster pavement distress data into homogeneous groups depending on the extent of distress and, second, to identify and assess the influence of a variety of exogenous variables on the extent of pavement distress. To achieve these objectives, a two-step clustering and classification evolutionary modular neural network is developed with a large (more than 1,000 observations) and recent (1998) data set collected from in-service pavements in 15 European countries. The results indicate that the extent of the cracking distress (magnitude of cracking) can be separated into five homogeneous clusters (with Cluster 1 suggesting very low cracking and Cluster 5 very extensive cracking), with different explanatory variables affecting the extent of cracking in each of these clusters.	en
heal.journalName	Transportation Research Record	en
dc.identifier.doi	10.3141/1970-24	en
dc.identifier.issue	1970	en
dc.identifier.spage	207	en
dc.identifier.epage	214	en