A DATA SCIENCE STUDY FOR DETERMINING FOOD QUALITY: AN APPLICATION TO WINE

被引：1

作者：

Ozalp, A. E. ^{[1
]}

Askerzade, I. N. ^{[2
]}

机构：

[1] Hacettepe Univ, Fac Sci, Dept Math, Ankara, Turkey

[2] Ankara Univ, Fac Engn, Dept Comp Engn, Ankara, Turkey

来源：

COMMUNICATIONS FACULTY OF SCIENCES UNIVERSITY OF ANKARA-SERIES A1 MATHEMATICS AND STATISTICS | 2019年 / 68卷 / 01期

关键词：

Adaptive Neuro Fuzzy Inference System; fuzzy logic; data science; random forest algorithm;

D O I：

10.31801/cfsuasmas.469131

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

In 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.

引用

页码：762 / 770

页数：9

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