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https://hdl.handle.net/1822/63233
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Campo DC | Valor | Idioma |
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dc.contributor.author | Martins, Francisco F. | por |
dc.contributor.author | Camões, Aires | por |
dc.date.accessioned | 2020-01-16T10:46:09Z | - |
dc.date.issued | 2019-11 | - |
dc.date.submitted | 2020-01 | - |
dc.identifier.citation | Martins F. F., Camões A. Prediction of Restrained Shrinkage Crack Width of Slag Mortar Composites Using Data Mining Techniques, Matária, Vol. 24, Issue 4, doi:10.1590/s1517-707620190004.0852, 2019 | por |
dc.identifier.issn | 1517-7076 | por |
dc.identifier.uri | https://hdl.handle.net/1822/63233 | - |
dc.description.abstract | The purpose of this study is to develop data mining models to predict restrained shrinkage crack widths of slag mortar cementitious composites. A database published by BILIR et al. [1] was used to develop these models. As a modelling tool R environment was used to apply these data mining (DM) techniques. Several algorithms were tested and analyzed using all the combinations of the input parameters. It was concluded that using one or three input parameters the artificial neural networks (ANN) models have the best performance. Nevertheless, the best forecasting capacity was obtained with the support vector machines (SVM) model using only two input parameters. Furthermore, this model has better predictive capacity than adaptative-network-based fuzzy inference system (ANFIS) model developed by BILIR et al. [1] that uses three input parameters. | por |
dc.description.sponsorship | FEDER funds through the Competitivity Factors Operational Programme -COMPETE and by national funds through FCT – Foundation for Science and Technology within the scope ofthe project POCI-01-0145-FEDER-007633” | por |
dc.language.iso | eng | por |
dc.publisher | Rede Latino-Americana de Materiais | por |
dc.rights | restrictedAccess | por |
dc.subject | Data Mining | por |
dc.subject | Mortar | por |
dc.subject | Prediction | por |
dc.subject | restrained shrinkage cracking | por |
dc.title | Prediction of restrained shrinkage crack width of slag mortar composites using data mining techniques | por |
dc.type | article | - |
dc.peerreviewed | yes | por |
dc.relation.publisherversion | http://www.scielo.br/scielo.php?pid=S1517-70762019000400345&script=sci_arttext | por |
dc.comments | http://ctac.uminho.pt/node/3077 | por |
oaire.citationIssue | 4 | por |
oaire.citationVolume | 24 | por |
dc.date.updated | 2020-01-15T17:48:07Z | - |
dc.identifier.doi | 10.1590/s1517-707620190004.0852 | por |
dc.date.embargo | 10000-01-01 | - |
dc.subject.fos | Engenharia e Tecnologia::Engenharia Civil | por |
dc.subject.wos | Science & Technology | por |
sdum.journal | Revista Matéria | por |
Aparece nas coleções: | C-TAC - Artigos em Revistas Internacionais |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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3077-1517-7076-rmat-24-04-e12527.pdf Acesso restrito! | 291,13 kB | Adobe PDF | Ver/Abrir |