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