Characterization of mixtures part 1: Prediction of infinite-dilution activity coefficients using neural network-based QSPR models

QSAR and Combinatorial Science

Volumn 27, Issue 11-12, 2008, Pages 1346-1361

  Ajmani, Subhash ^a,d   Rogers, Stephen C ^b   Barley, Mark H ^b   Burgess, Andrew N ^b   Livingstone, David J ^a,c  

^a UNIVERSITY OF PORTSMOUTH   (United Kingdom)

^b Wilton Centre   (United Kingdom)

^c ChemQuest   (United Kingdom)

^d VLife Sciences Technologies   (India)

Author keywords

Dual response model; Ensemble Neural Network; Mixtures; Neural Network; QSPR

Indexed keywords

BINARY MIXTURES; COMPUTATIONAL CHEMISTRY;

DESCRIPTORS; DUAL-RESPONSE; DUAL-RESPONSE MODEL; ENSEMBLE NEURAL NETWORK; INFINITE-DILUTION ACTIVITY COEFFICIENTS; NETWORK-BASED; NEURAL-NETWORKS; QSPR; QSPR MODEL; RESPONSE MODEL;

NEURAL NETWORKS;

CHEMICAL COMPOUND;

ANALYTIC METHOD; ANALYTICAL PARAMETERS; AQUEOUS SOLUTION; ARTICLE; ARTIFICIAL NEURAL NETWORK; CHEMICAL ANALYSIS; DILUTION; LIQUID; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; PHYSICAL CHEMISTRY; PREDICTION; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE PROPERTY RELATION; SAMPLING; STATISTICAL MODEL;

EID: 58149116742     PISSN: 1611020X     EISSN: 16110218     Source Type: Journal    
DOI: 10.1002/qsar.200860022     Document Type: Article

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