Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/18957

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dc.contributor.authorRibeiro, Jorge Manuel Ferreira Barbosa-
dc.contributor.authorNeves, José-
dc.contributor.authorSanchez, Juan-
dc.contributor.authorFernández-Delgado, Manuel-
dc.contributor.authorMachado, José Manuel-
dc.contributor.authorNovais, Paulo-
dc.date.accessioned2012-04-27T14:03:08Z-
dc.date.available2012-04-27T14:03:08Z-
dc.date.issued2009-
dc.identifier.isbn978-960-474-088-8-
dc.identifier.issn1790-5117por
dc.identifier.urihttp://hdl.handle.net/1822/18957-
dc.description.abstractThe vinification process is one important stages of the wines production that can influence the achievement of wines quality. Based in a chemical samples this assessment is traditionally realized by wine tasters that analyze some subjective parameters such as colour, foam, flavour and savour. This type of analysis is very important for the production of wine and for its successful marketing. The use of Data Mining techniques in this field has a great relevance in revealing the importance of the numerous chemical parameters involved in the process of wine production, as well as to define models to classify classes of parameters for example, to determine the organoleptic parameters based on chemical parameters of the winemaking process. This paper presents the Decision Trees, Artificial Neural Networks and Linear Regression as Data Mining techniques to achieve the objectives of classification and regression in order to create models to predict the organoleptic parameters from the chemical parameters of the vinification process. The experiments were oriented using the new Microsoft's SQL Server 2008 Business Intelligence Development and an open-source Data Mining tool (WEKA). Very good results were achieved with accuracies between 86% and 99% obtained for all models.por
dc.language.isoengpor
dc.publisherWorld Scientific and Engineering Academy and Society (WSEAS)por
dc.rightsrestrictedAccesspor
dc.subjectData Miningpor
dc.subjectKnowledge Discovery in Databasespor
dc.subjectDecision Treespor
dc.subjectArtificial Neural Networkspor
dc.subjectLinear Regressionpor
dc.subjectWine Vinification Processpor
dc.titleWine vinification prediction using data mining toolspor
dc.typeconferencePaper-
dc.peerreviewedyespor
oaire.citationConferenceDate26-28 Junho 2009-
sdum.event.locationTbilisi, Georgia-
oaire.citationStartPage78por
oaire.citationEndPage85por
oaire.citationTitleComputing and Computational Intelligence : proceedings of the 2009 European Computing Conference (ECC '09) and the 3rd International Conference on Computational Intelligence (CI '09)por
dc.subject.wosScience & Technologypor
sdum.conferencePublicationComputing and Computational Intelligence : proceedings of the 2009 European Computing Conference (ECC '09) and the 3rd International Conference on Computational Intelligence (CI '09)-
Appears in Collections:DI/CCTC - Artigos (papers)

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