Application of Potential Type Electronic Tongue on Milk Discrimination

Jinguo Zhang (Power Distribution and Transformation Technical College)
Chun Pan (Northeast Dianli University)
Honghui Gao (Northeast Dianli University)
Hong Men (Northeast Dianli University)
Yitong Li (Beijing University of Posts and Telecommunications)

Indonesian Journal of Electrical Engineering and Computer Science
Vol 11, No 9: September 2013

Four brands of milk based on the potential type electronic tongue are tested by using the principal component analysis (PCA), fuzzy c-means clustering (FCM) algorithm for clustering analysis. Support vector machine (SVM) algorithm is used to forecast category for any brand of milk data, which are extracted from all the data randomly. The results show that potential type electronic tongue can distinguish four brands of milk perfectly, and the forecasting accuracy rate can reach to 100%. Potential type electronic tongue has potential application value in the identification of milk. DOI: http://dx.doi.org/10.11591/telkomnika.v11i9.3292