Quantitative predictions of gas chromatography retention indexes with support vector machines, radial basis neural networks and multiple linear regression

Analytica Chimica Acta

Volumn 609, Issue 1, 2008, Pages 24-36

  Chen, Hai Feng ^a  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

Author keywords

Gas chromatography retention index; Multiple linear regression; Radial basis neural networks; Support vector machines

Indexed keywords

CORRELATION METHODS; GAS CHROMATOGRAPHY; LINEAR REGRESSION; MATHEMATICAL MODELS; SUPPORT VECTOR MACHINES;

CORRELATION COEFFICIENT; RADIAL BASIS NEURAL NETWORKS; RETENTION INDEX; STATISTICAL MODELS;

RADIAL BASIS FUNCTION NETWORKS;

BENZOIC ACID DERIVATIVE; BICYCLO COMPOUND; CYCLOHEXANE DERIVATIVE; CYCLOHEXENE DERIVATIVE; CYCLOOCTANE DERIVATIVE; CYCLOPENTADIENE DERIVATIVE; CYCLOPENTANE DERIVATIVE; CYCLOPENTENE DERIVATIVE; CYCLOPROPANE DERIVATIVE; NAPHTHALENE DERIVATIVE; ORGANIC COMPOUND;

ARTICLE; CHEMICAL STRUCTURE; EXPERIMENTAL DESIGN; GAS CHROMATOGRAPHY; INTERMETHOD COMPARISON; MULTIPLE LINEAR REGRESSION ANALYSIS; NERVE CELL NETWORK; PHYSICAL CHEMISTRY; PRIORITY JOURNAL; QUANTITATIVE ANALYSIS; QUANTITATIVE STRUCTURE ACTIVITY RELATION; QUANTITATIVE STRUCTURE PROPERTY RELATION; STATISTICAL MODEL;

CHROMATOGRAPHY, GAS; LINEAR MODELS; MOLECULAR STRUCTURE; NEURAL NETWORKS (COMPUTER);

EID: 38549170542     PISSN: 00032670     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.aca.2008.01.003     Document Type: Article

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