Classification of raw and roasted semen cassiae samples with the use of fourier transform infrared fingerprints and least squares support vector machines

Applied Spectroscopy

Volumn 64, Issue 6, 2010, Pages 649-656

  Lai, Yanhua ^a   Ni, Yongnian ^a   Kokot, Serge ^b  

^a NANCHANG UNIVERSITY   (China)

^b QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

Author keywords

ANNs; Chemometrics; Infrared spectroscopy; Kernel principal component analysis; Least squares support vector machines; PCA; Radial basis function artificial neural networks; Semen cassiae; Traditional chinese medicine

Indexed keywords

BODY FLUIDS; COMPLEX NETWORKS; DEEP NEURAL NETWORKS; FUNCTIONS; INFRARED SPECTROSCOPY; MEDICINE; NEURAL NETWORKS; RADIAL BASIS FUNCTION NETWORKS; SUPPORT VECTOR MACHINES; VECTORS;

ANNS; CHEMOMETRICS; KERNEL PRINCIPAL COMPONENT ANALYSES (KPCA); LEAST SQUARES SUPPORT VECTOR MACHINES; RADIAL BASIS FUNCTION ARTIFICIAL NEURAL NETWORKS; SEMEN CASSIAE; TRADITIONAL CHINESE MEDICINE;

PRINCIPAL COMPONENT ANALYSIS;

HERBACEOUS AGENT;

ARTIFICIAL INTELLIGENCE; CHEMISTRY; FABACEAE; INFRARED SPECTROSCOPY; PLANT SEED; PROCEDURES; REGRESSION ANALYSIS;

ARTIFICIAL INTELLIGENCE; DRUGS, CHINESE HERBAL; FABACEAE; LEAST-SQUARES ANALYSIS; SEEDS; SPECTROSCOPY, FOURIER TRANSFORM INFRARED;

EID: 77953863609     PISSN: 00037028     EISSN: None     Source Type: Journal    
DOI: 10.1366/000370210791414362     Document Type: Article

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