title: [Artificial neural networks for the identification of infrared spectra of Ilex Kudingcha].
abstract: In order to identify Ilex Kudingcha, two kinds of models of artificial neural networks (ANN), i.e. competitive neural network and back propagation neural network, were used to analyze their infrared spectra. Ilex Kudingcha samples were collected by Fourier transform infrared (FTIR) spectra. Twenty five samples were gathered as a train set, and 11 samples as a test set, then their training was performed using two networks each. The results show that the identification of Ilex Kudingcha from different areas can be effectively performed with the competitive neural network and BP network, but the competitive neural network is used in the identification of different grades of Ilex Kudingcha. The results were better in training speed and accuracy with the competitive neural network. In conclusion, the competitive neural network combined with FTIR spectroscopy is a good method for the identification of Ilex Kudingcha.
authors.affiliation: Center of Analysis and Test, Shanxi Normal University, Linfen 041004, China.
authors.forename: Tao-Tao
authors.initials: TT
authors.lastname: Pang
authors.forename: Jian-Bin
authors.initials: JB
authors.lastname: Yao
authors.forename: Li-Ming
authors.initials: LM
authors.lastname: Du
mesh_terms: D000465:Algorithms; D001628:Beverages / Q000032:analysis* / Q000592:standards; D002681:China; D005843:Geography; D030017:Ilex / Q000737:chemistry*; D016571:Neural Networks, Computer; D012015:Reference Standards; D015203:Reproducibility of Results; D017550:Spectroscopy, Fourier Transform Infrared / Q000379:methods*