Rapid identification of waste cooking oil with near infrared spectroscopy based on support vector machine

IFIP Advances in Information and Communication Technology

Volumn 392 AICT, Issue PART 1, 2013, Pages 11-18

  Shen, Xiong ^a   Zheng, Xiao ^a   Song, Zhiqiang ^a   He, Dongping ^a   Qi, Peishi ^b  

^a WUHAN POLYTECHNIC UNIVERSITY   (China)

^b Pashun Group   (China)

Author keywords

near infrared spectroscopy; parameters optimization; support vector machine; waste cooking oil

Indexed keywords

CLASSIFICATION MODELS; CROSS VALIDATION; EDIBLE VEGETABLE OIL; GA OPTIMIZATION; K-MEANS; KERNEL FUNCTION; KERNEL FUNCTION PARAMETERS; LINEAR DISCRIMINANT ANALYSIS; PARAMETERS OPTIMIZATION; PENALTY PARAMETERS; PRINCIPAL COMPONENTS; QUALITATIVE MODEL; RADIAL BASIS FUNCTION(RBF); RAPID IDENTIFICATION; RECOGNITION RATES; SPECTRAL PRE TREATMENTS; TRAINING SETS; VECTOR NORMALIZATION; WASTE COOKING OIL; WASTE OIL;

AGRICULTURE; IMAGE RETRIEVAL; NEAR INFRARED SPECTROSCOPY; PARTICLE SWARM OPTIMIZATION (PSO); PRINCIPAL COMPONENT ANALYSIS; RADIAL BASIS FUNCTION NETWORKS; THERMAL PROCESSING (FOODS); VEGETABLE OILS;

SUPPORT VECTOR MACHINES;

EID: 84874549781     PISSN: 18684238     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-36124-1_2     Document Type: Conference Paper

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