• 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