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    Prediction of Restrained Shrinkage Crack Width of Slag Mortar Composites Using Data Mining Techniques

    TitlePrediction of Restrained Shrinkage Crack Width of Slag Mortar Composites Using Data Mining Techniques
    Publication TypePapers in International Journals
    Year of Publication2019
    AuthorsMartins F. F., and Camões A.
    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.

    JournalMatéria
    Volume24
    Issue4
    Date Published2019-11-25
    PublisherScielo
    ISSN1517-7076
    DOI10.1590/s1517-707620190004.0852
    URLhttp://www.scielo.br/scielo.php?pid=S1517-70762019000400345&script=sci_arttext
    KeywordsData Mining, Mortar, Prediction, restrained shrinkage cracking
    RightsrestrictedAccess
    Peer reviewedyes
    Statuspublished
    • Google Scholar
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    About CTAC

    The Centre for Territory, Environment and Construction (CTAC) is a research unit of the School of Engineering of University of Minho (UMinho), recognised by the “FCT – Fundação para a Ciência e Tecnologia” (Foundation for Science and Technology), associated to the Department of Civil Engineering (DEC), with whom it shares resources and namely human resources.

    Currently CTAC aggregates 24 researchers holding a PhD of which 20 are faculty professors of the Civil Engineering Department. Read more


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