Fuzzy ARTMAP for the Adulterated Honey Discrimination with Voltammetric Electronic Tongue

• Main Authors: Hong Men, Honghui Gao, Jingyi Li, Jingjing Liu, Yanping Zhang
• Format: Article
• Language: English
• Published: IFSA Publishing, S.L. 2014-09-01
• Series: Sensors & Transducers
• Subjects: Fuzzy ARTMAP; Voltammetric electronic tongue; Honey Adulteration; PLS; RBF; FKNN.
• Online Access: http://www.sensorsportal.com/HTML/DIGEST/september_2014/Vol_178/P_2350.pdf
• ISSN: 2306-8515; 1726-5479

In this paper, in order to improve recognition rate of the Jing Hua honey by adding different proportions of glucose, the pattern recognition methods of Radial Basis Function (RBF), Fuzzy k-nearest neighbor algorithm (FKNN) and Fuzzy Adaptive Resonance Theory MAP (Fuzzy ARTMAP) were used to classify the different honey adulterated proportion. The result shows that the recognition effect by using Fuzzy ARTMAP to discriminate the different concentration honey adulteration is better than RBF neural network and FKNN, and the recognition rate improved from 83.33 % to 94.40 %, and the discriminated speed of using Fuzzy ARTMAP is faster than RBF and FKNN. Fuzzy ARTMAP is a kind of recognition method which allows for fast and reliable. In addition, the prediction of honey adulterated proportion can be realized by The Partial Least Square (PLS).