计算机工程与应用Issue(2)：175-179,5.DOI:10.3778/j.issn.1002-8331.1401-0355
葡萄酒的模糊C均值聚类及其最优聚类选择
Fuzzy c-means algorithm and optimal numbers of clus-ters for wine
摘要
Abstract
Popular method of wine classification is to invite wine tasters to taste the waited classification wine and give scores. This approach is influenced greatly by the subjective reasons of the wine tasters, and leads to uncertainty appear. Based on the evaluation of wine classification, an objective method is given. This approach depends on the mainly physi-cochemical indexes of wines which decide surface, mouth feel and fragrance, fuzzy c-means algorithm, F-statistical quan-tity and its significance level. Original data of wine is used to check the validity of the method with MATLAB program. This approach overcomes the deficiency of the existed methods, objectively evaluates wine quality, and proposes an alter-native for wine classification.关键词
葡萄酒/理化指标/模糊C均值聚类/F统计量Key words
wine/physicochemical index/fuzzy c-means algorithm/F-statistical quantity分类
数理科学引用本文复制引用
黄春娥,张洪,张景胜,孙明星,叶志伟..葡萄酒的模糊C均值聚类及其最优聚类选择[J].计算机工程与应用,2016,(2):175-179,5.基金项目
国家自然科学基金面上项目（No.71373023）。 （）
