| 基于物理化学性质的葡萄酒质量的可视化评价研究 |
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| 引用本文： | 王金甲,尹涛,李静,洪文学,马崇霄. 基于物理化学性质的葡萄酒质量的可视化评价研究[J]. 东北重型机械学院学报, 2010, 0(2): 133-137 |
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| 作者姓名： | 王金甲 尹涛 李静 洪文学 马崇霄 |
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| 作者单位： | [1]燕山大学电气工程学院,河北秦皇岛066004 [2]燕山大学信息科学与工程学院,河北秦皇岛066004 [3]燕山大学理学院,河北秦皇岛066004 [4]河北科技师范学院机电工程学院,河北昌黎066000 |
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| 基金项目： | 国家自然科学基金资助项目（60405035,60904100） |
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| 摘 要： | 提出了一种可视化的方法评价葡萄酒质量。葡萄酒数据来自于认证阶段的物理化学分析测试，其中输入变量是11个，输出变量是葡萄酒质量，共得到1599个的红葡萄酒样本和4898个的白葡萄酒样本。结果表明该方法的效果优于传统的神经网络和支持向量机方法，并且具有可视化的优点。这对于改进酿酒品酒评价和葡萄酒生产都有重要意义，并且对根据消费者口味细分目标市场也很有帮助。
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| 关 键 词： | 评价 可视化 支持向量机 神经网络 多元数据图表示 |
Visual evaluation of wine quality from physicochemical properties |
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| WANG Jin-jia,YIN Tao,LI Jing,HONG Wen-xue,MA Chong-xiao. Visual evaluation of wine quality from physicochemical properties[J]. , 2010, 0(2): 133-137 |
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| Authors: | WANG Jin-jia YIN Tao LI Jing HONG Wen-xue MA Chong-xiao |
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| Affiliation: | 1. College of Electrical Engineering, Yanshan University, Qinhuangdao, Hebei 066004, China; 2. College of Information Science and Engineer, Yanshan University, Qinhuangdao, Hebei 066004, China; 3. College of Sciences, Yanshan University, Qinhuangdao, Hebei 066004, China; 4. College of Mechanical and Electrical Engineering, Hebei Normal University of Science and Technology, Changli, Hebei 066000, China) |
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| Abstract: | A visualization method of evaluation of wine quality is proposed. The wine data are from the certification phase of the physicochemical analysis test. The data include the 11 input variables, an output variable which is the quality of wine. The data include 1 599 samples of red wine and 4 898 samples of white wine. The result proves that the visualization method works better than the traditional neural networks and support vector machine method, and has visual advantages. Such model is useful to support the oenologist wine tasting evaluations and improve wine production. Furthermore, similar techniques can help in target marketing by modeling consumer tastes from niche markets. |
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| Keywords: | evaluation visualization support vector machines neural networks graphical representation of the multivariate data |
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