A data science study for determining food quality: an application to wine

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dc.contributor.authorÖzalp, Ata Emre
dc.contributor.authorAskerzade, İman
dc.contributor.departmentBilgisayar Mühendisliğitr_TR
dc.contributor.facultyMühendislik Fakültesitr_TR
dc.date.accessioned2021-11-02T06:59:02Z
dc.date.available2021-11-02T06:59:02Z
dc.date.issued2019-02-01
dc.description.abstractIn this paper, wine quality is investigated based on physicochemical ingredients which include fixed acidity, volatile acidity, citric acid, residual sugar, chloride, free sulfur dioxide, total sulfur dioxide, density, pH, sulphate and alcohol, by ANFIS (Adaptive Neuro Fuzzy Inference System) method and by random forest algorithm which is a powerful classification algorithm. Although this study specifically investigate the relation between physicochemical ingredients and the quality of wine, the results can be adaped to determination of the quality of any food product in terms of the ingredients.tr_TR
dc.description.indexTrdizintr_TR
dc.identifier.endpage770tr_TR
dc.identifier.issn/e-issn2618-6470
dc.identifier.issue1tr_TR
dc.identifier.startpage762tr_TR
dc.identifier.urihttps://doi.org/10.31801/cfsuasmas.469131tr_TR
dc.identifier.urihttp://hdl.handle.net/20.500.12575/75818
dc.identifier.volume68tr_TR
dc.language.isoentr_TR
dc.publisherAnkara Üniversitesi Fen Fakültesitr_TR
dc.relation.isversionof10.31801/cfsuasmas.469131tr_TR
dc.relation.journalCommunications Faculty of Sciences University of Ankara Series A1 Mathematics and Statisticstr_TR
dc.relation.publicationcategoryGazete Makalesi - Ulusaltr_TR
dc.subjectAdaptive Neuro Fuzzy Inference Systemtr_TR
dc.subjectFuzzy logictr_TR
dc.subjectData sciencetr_TR
dc.titleA data science study for determining food quality: an application to winetr_TR
dc.typeArticletr_TR

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Cilt:68 Sayı:01 (2019)