Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/44912

TitleUsing data mining algorithms to predict the bond strength of NSM FRP systems in concrete
Author(s)Coelho, Mário Rui Freitas
Sena-Cruz, José
Neves, Luís A. C.
Pereira, Marta
Cortez, Paulo
Miranda, Tiago F. S.
KeywordsNSM
Bond
FRP
Guidelines
Data Mining
Issue date2016
PublisherElsevier Sci Ltd
JournalConstruction and Building Materials
CitationCoelho, M. R. F., Sena-Cruz, J. M., Neves, L. A. C., Pereira, M., Cortez, P., & Miranda, T. (2016). Using data mining algorithms to predict the bond strength of NSM FRP systems in concrete. Construction and Building Materials, 126, 484-495. doi: 10.1016/j.conbuildmat.2016.09.048
Abstract(s)This paper presents the effectiveness of soft computing algorithms in analyzing the bond behavior of fiber reinforced polymer (FRP) systems inserted in the cover of concrete elements, commonly known as the near-surface mounted (NSM) technique. It focuses on the use of Data Mining (DM) algorithms as an alternative to the existing guidelines’ models to predict the bond strength of NSM FRP systems. To ease and spread the use of DM algorithms, a web-based tool is presented. This tool was developed to allow an easy use of the DM prediction models presented in this work, where the user simply provides the values of the input variables, the same as those used by the guidelines, in order to get the predictions. The results presented herein show that the DM based models are robust and more accurate than the guidelines’ models and can be considered as a relevant alternative to those analytical methods.
Typearticle
URIhttp://hdl.handle.net/1822/44912
DOI10.1016/j.conbuildmat.2016.09.048
ISSN0950-0618
e-ISSN1879-0526
Peer-Reviewedyes
AccessopenAccess
Appears in Collections:ISISE - Artigos em Revistas Internacionais

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