利用MLP网络对电子舌头的红酒和水读数进行分类

H. C. D. Sousa, A. Riul
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引用次数: 13

摘要

通过“人造舌头”来模仿人类的味觉系统已经做出了可行的努力。该装置包括一系列能够以比生物系统更高的灵敏度区分味道的传感单元。实验结果表明,当这些传感单元产生的数据被人工神经网络处理后,这种“人工舌头”可以成功地区分不同酿酒师、年份和葡萄的葡萄酒,以及不同品牌的矿泉水、蒸馏水和milliq水。实验结果表明,该传感装置可用于检测生产线中的异常化学物质,甚至为食品工业的质量标准控制提供了一种新的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using MLP networks to classify red wines and water readings of an electronic tongue
Feasible efforts have been made to mimic the human gustatory system through an "artificial tongue". This device comprises an array of sensing units that is able to differentiate tastes with a higher sensitivity than the biological system. Experimental results indicate that when the data generated by such sensing units are handled by artificial neural networks, this "artificial tongue" can successfully discriminate wines of different winemakers, vintage and grapes, as well as different brands of mineral water, distilled water and Milli-Q water. The accuracy achieved by the experiments suggests that the sensing units may be used to detect abnormal chemical substances in a production line or even set a new approach to control quality standards in food industry.
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