Using MLP networks to classify red wines and water readings of an electronic tongue

被引:2
|
作者
de Sousa, HC [1 ]
Carvalho, ACPLF [1 ]
Riul, A [1 ]
Mattoso, LHC [1 ]
机构
[1] Univ Sao Paulo, Inst Ciencias Matemat & Computacao, BR-13560970 Sao Carlos, SP, Brazil
来源
VII BRAZILIAN SYMPOSIUM ON NEURAL NETWORKS, PROCEEDINGS | 2002年
关键词
D O I
10.1109/SBRN.2002.1181428
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:13 / 18
页数:6
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