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Evaluation of Sensorial Qualities of Fruit Wines by Kohonen Neural Network

机译：科霍恩神经网络评价水果葡萄酒的感觉素质

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摘要

Sensorial qualities of fruit wines were compared by clustering due artificial neural networks. A Kohonen network has been used as a software tool in order to increase the human skills in this kind of application. Seven wine samples were used in this work, which the five samples were of Barbados cherry wine, one sample of peach wine and one sample of grape wine. 50 consumers chosen to perhaps had been used to obtain the sensorial data using a hedonic scale of 1-9 times. Sensorial values of flavor, aroma and appearance obtained of the hedonic dating were compared. Results showed that Kohonen network classified the Barbados cherry wines in distinct group, for frequency among yours sensorial responses. Kohonen network results were similar or better than statistical classification, this shows that the use of Kohonen algorithm in the sensorial analysis of wines is valid. Kohonen algorithm is very good in clustering of Barbados cherry wine samples and it uses in sensorial analyses of wines is promises.
机译：果酒的感官品质是由由于人工神经网络的集群相比。一个Kohonen网络的是为了提高人的技能，在这种应用中被用来作为一个软件工具。七酒样在这项工作中，这五个样品的巴巴多斯樱桃酒，水蜜桃酒一个样本和葡萄酒一个样本使用。 50名消费者选择以或许已经使用利用的1-9倍嗜好程度以获得感官数据。风味，香气和享乐约会获得外观的感官值进行比较。结果表明，Kohonen神经网络分类在不同的组巴巴多斯樱桃葡萄酒，为你的感官响应之中频率。 Kohonen网络的结果是相似的或比统计分类好，这说明葡萄酒的感官分析中的应用Kohonen的算法是有效的。 Kohonen的算法是在巴巴多斯樱桃酒样品进行聚类非常好，它的葡萄酒感官分析采用的是承诺。

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