Using data mining algorithms to predict the bond strength of NSM FRP systems in concrete
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...
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| Format: | Article |
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Elsevier
2016
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| Online Access: | https://eprints.nottingham.ac.uk/40378/ |
| _version_ | 1848796042088153088 |
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| author | Coelho, Mário R.F. Sena-Cruz, José M. Neves, Luís A.C. Pereira, Marta Cortez, Paulo Miranda, Tiago |
| author_facet | Coelho, Mário R.F. Sena-Cruz, José M. Neves, Luís A.C. Pereira, Marta Cortez, Paulo Miranda, Tiago |
| author_sort | Coelho, Mário R.F. |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T19:41:41Z |
| format | Article |
| id | nottingham-40378 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:41:41Z |
| publishDate | 2016 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-403782020-05-04T18:20:57Z https://eprints.nottingham.ac.uk/40378/ Using data mining algorithms to predict the bond strength of NSM FRP systems in concrete Coelho, Mário R.F. Sena-Cruz, José M. Neves, Luís A.C. Pereira, Marta Cortez, Paulo Miranda, Tiago 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. Elsevier 2016-11-15 Article PeerReviewed Coelho, Mário R.F., Sena-Cruz, José M., Neves, Luís A.C., Pereira, Marta, Cortez, Paulo and Miranda, Tiago (2016) Using data mining algorithms to predict the bond strength of NSM FRP systems in concrete. Construction and Building Materials, 126 . pp. 484-495. ISSN 1879-0526 FRP; NSM; Bond; Guidelines; Data Mining http://www.sciencedirect.com/science/article/pii/S095006181631488X doi:10.1016/j.conbuildmat.2016.09.048 doi:10.1016/j.conbuildmat.2016.09.048 |
| spellingShingle | FRP; NSM; Bond; Guidelines; Data Mining Coelho, Mário R.F. Sena-Cruz, José M. Neves, Luís A.C. Pereira, Marta Cortez, Paulo Miranda, Tiago Using data mining algorithms to predict the bond strength of NSM FRP systems in concrete |
| title | Using data mining algorithms to predict the bond strength of NSM FRP systems in concrete |
| title_full | Using data mining algorithms to predict the bond strength of NSM FRP systems in concrete |
| title_fullStr | Using data mining algorithms to predict the bond strength of NSM FRP systems in concrete |
| title_full_unstemmed | Using data mining algorithms to predict the bond strength of NSM FRP systems in concrete |
| title_short | Using data mining algorithms to predict the bond strength of NSM FRP systems in concrete |
| title_sort | using data mining algorithms to predict the bond strength of nsm frp systems in concrete |
| topic | FRP; NSM; Bond; Guidelines; Data Mining |
| url | https://eprints.nottingham.ac.uk/40378/ https://eprints.nottingham.ac.uk/40378/ https://eprints.nottingham.ac.uk/40378/ |