Self-Organizing Maps and Support Vector Regression as aids to coupled chromatography: Illustrated by predicting spoilage in apples using volatile organic compounds

Talanta

Volumn 83, Issue 4, 2011, Pages 1269-1278

  Fong, Sim S ^a   Sági Kiss, Virág ^b   Brereton, Richard G ^a  

^a UNIVERSITY OF BRISTOL   (United Kingdom)

^b Institute of Entrepreneurship and Innovation   (Hungary)

Author keywords

Food spoilage; Gas chromatography mass spectrometry; Pattern recognition; Self Organizing Maps; Support Vector Regression; Volatile organic compounds

Indexed keywords

BIOLOGY; CONFORMAL MAPPING; EVOLUTIONARY ALGORITHMS; FRUITS; LEARNING SYSTEMS; MASS SPECTROMETRY; OPTIMIZATION; PATTERN RECOGNITION; REGRESSION ANALYSIS; SELF ORGANIZING MAPS; SPOILAGE; VOLATILE ORGANIC COMPOUNDS;

DIFFERENTIAL EVOLUTION; FOOD SPOILAGE; GAS CHROMATOGRAPHY-MASS SPECTROMETRY; MACHINE LEARNING METHODS; PENICILLIUM EXPANSUM; SOLID-PHASE MICROEXTRACTION; SUPPORT VECTOR REGRESSION (SVR); TWO-DIMENSIONAL MAP;

GAS CHROMATOGRAPHY;

EID: 79251595806     PISSN: 00399140     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.talanta.2010.06.051     Document Type: Article

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