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dc.contributor.convenorBijan Samali, Mario M. Attard and Chongmin Song
dc.contributor.authorBu, GP
dc.contributor.authorLee, JH
dc.contributor.authorGuan, H
dc.contributor.authorLoo, YC
dc.contributor.editorBijan Samali, Mario M. Attard & Chongmin Song
dc.date.accessioned2017-05-03T15:03:59Z
dc.date.available2017-05-03T15:03:59Z
dc.date.issued2013
dc.date.modified2013-10-30T03:42:46Z
dc.identifier.isbn9780415633185
dc.identifier.refurihttp://acmsm.org/
dc.identifier.doi10.1201/b15320-158
dc.identifier.urihttp://hdl.handle.net/10072/53900
dc.description.abstractIn order to minimise the shortcomings of insufficient inspection records, an integrated and enhanced bridge deterioration method using a combination of state-based and time-based probabilistic techniques has recently been developed. It has demonstrated an improved performance as compared to the standalone probabilistic techniques. Nevertheless certain shortcomings still remain in the integrated method which necessities further improvement. In this study, the core component of the state-based modeling is replaced by an Elman Neural Networks (ENN). The integrated method incorporated with ENN is more effective in predicting long-term bridge performance as compared to the typical deterministic deterioration modeling techniques. As part of a comprehensive case study program, this paper presents the deterioration prediction of 35 bridge elements with material types of cast-in-situ Concrete (C) and Precast concrete (P). These elements are selected from 86 bridges (totaling 1,855 inspection records). The enhanced reliability of the proposed integrated method incorporating ENN is confirmed.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.languageEnglish
dc.publisherCRC Press
dc.publisher.placeUnited States
dc.publisher.urihttp://acmsm.org/
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofconferencenameACMSM 22
dc.relation.ispartofconferencetitleFrom Materials to Structures: Advancement Through Innovation - Proceedings of the 22nd Australasian Conference on the Mechanics of Structures and Materials, ACMSM 2012
dc.relation.ispartofdatefrom2012-12-11
dc.relation.ispartofdateto2012-12-14
dc.relation.ispartoflocationSydney, Australia
dc.relation.ispartofpagefrom885
dc.relation.ispartofpageto889
dc.rights.retentionY
dc.subject.fieldofresearchInfrastructure engineering and asset management
dc.subject.fieldofresearchcode400508
dc.titleIntegrated Bridge Deterioration Modeling for Concrete Elements Incorporating Elman Neural Network
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
gro.facultyGriffith Sciences, Griffith School of Engineering
gro.date.issued2013
gro.hasfulltextNo Full Text
gro.griffith.authorLoo, Yew-Chaye
gro.griffith.authorGuan, Hong


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    Contains papers delivered by Griffith authors at national and international conferences.

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