DocumentCode :
3207627
Title :
Using MLP networks to classify red wines and water readings of an electronic tongue
Author :
De Sousa, Humberto Costa ; Carvalho, André C P L F ; Riul, Antonio, Jr. ; Mattoso, Luiz H C
Author_Institution :
Instituto de Ciencias Matematicas a de Computacao, Univ. of Sao Paulo, Sao Carlos, Brazil
fYear :
2002
fDate :
2002
Firstpage :
13
Lastpage :
18
Abstract :
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.
Keywords :
backpropagation; brewing industry; chemical sensors; multilayer perceptrons; pattern classification; artificial tongue; backpropagation; chemical sensor; multilayer perceptron; neural networks; wine classification; wine making; Artificial neural networks; Biological systems; Chemical industry; Chemical products; Food industry; Humans; Minerals; Pipelines; Production; Tongue;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2002. SBRN 2002. Proceedings. VII Brazilian Symposium on
Print_ISBN :
0-7695-1709-9
Type :
conf
DOI :
10.1109/SBRN.2002.1181428
Filename :
1181428
Link To Document :
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