The application of an artificial neural network in the identification of medicinal rhubarbs by near-infrared spectroscopy

Phytochemical Analysis

Volumn 13, Issue 5, 2002, Pages 272-276

  Xiang, Lan ^a   Fan, Guoqiang ^b   Li, Junhui ^c   Kang, Hui ^a   Yan, Lu ^c   Zheng, Junhua ^a   Guo, Dean ^a  

^a PEKING UNIVERSITY HEALTH SCIENCE CENTER   (China)

^b Scientific Research Institute of Chinese Materia Medica   (China)

^c CHINA AGRICULTURAL UNIVERSITY   (China)

Author keywords

Back propagation neural network; Identification; Near infrared spectroscopy; Official rhubarbs; Unofficial rhubarbs

Indexed keywords

BACKPROPAGATION; INFRARED DEVICES; NEURAL NETWORKS;

BACK-PROPAGATION NEURAL NETWORKS; IDENTIFICATION; INPUT NODE; LEARNING RATES; OFFICIAL RHUBARB; PREDICTION ACCURACY; RECOGNITION ACCURACY; TEST SETS; TRAINING SETS; UNOFFICIAL RHUBARB;

NEAR INFRARED SPECTROSCOPY;

RHUBARB EXTRACT;

ACCURACY; ARTICLE; ARTIFICIAL NEURAL NETWORK; CHEMICAL PROCEDURES; CONTROLLED STUDY; DRUG IDENTIFICATION; MEDICINAL PLANT; METHODOLOGY; NEAR INFRARED SPECTROSCOPY; PREDICTION; RHUBARB; SAMPLING; SPECIES DIVERSITY; SPECIES IDENTIFICATION; CHEMISTRY; CLASSIFICATION; INFRARED SPECTROPHOTOMETRY;

NEURAL NETWORKS (COMPUTER); RHEUM; SPECTROPHOTOMETRY, INFRARED;

EID: 0036742229     PISSN: 09580344     EISSN: None     Source Type: Journal    
DOI: 10.1002/pca.654     Document Type: Article

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