Recognition of Mineral Water with an Electronic Tongue Based on PCA and PNN

Abstract:

Electronic Tongue is a kind of intelligent equipment which is used to distinguish tastes. An electronic tongue composed of a sensor array of ion-selective electrodes has been developed and used for the qualitative analysis of five different brands of mineral water. The acquired original data has been optimized by principal component analysis (PCA) and then the probabilistic neural network (PNN) model is designed to process the data. The application results show that the performance of the proposed method has surpasses the traditional BP neural network algorithm, the speed of recognition is fast and the accuracy rate can reach 100%, which gives the electronic tongue system good practicability and feasibility.

• Periodical: Key Engineering Materials (Volumes 467-469)
• Pages: 888-893
• DOI: https://doi.org/10.4028/www.scientific.net/KEM.467-469.888
• Online since: February 2011
• Authors: Hong Men, Yu Ming Guo, Rui Xia Wen, Bin Zhu
• Keywords: Electronic Tongue, Principal Component Analysis (PCA), Probabilistic Neural Network (PNN)

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