Characterization of mixtures. Part 2: QSPR models for prediction of excess molar volume and liquid density using neural networks

Molecular Informatics

Volumn 29, Issue 8-9, 2010, Pages 645-653

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

^a UNIVERSITY OF PORTSMOUTH   (United Kingdom)

^b AKZONOBEL   (United Kingdom)

^c UNIVERSITY OF MANCHESTER   (United Kingdom)

^d Delamere House   (United Kingdom)

^e NovaLead Pharma Pvt Ltd   (India)

Author keywords

Ensemble neural network; Excess molar volume; Mixtures; Neural network; QSPR

Indexed keywords

FORECASTING; HYDROGEN BONDS; THERMODYNAMIC PROPERTIES; VOLUME MEASUREMENT;

DESCRIPTORS; ENSEMBLE NEURAL NETWORK; EXCESS MOLAR VOLUMES; LIQUID DENSITY; MIXTURE PROPERTIES; NEURAL-NETWORKS; QSPR; QSPR MODEL; SINGLE COMPONENTS; VOLUME DENSITY;

BINARY MIXTURES;

HYDROGEN;

ARTICLE; ARTIFICIAL NEURAL NETWORK; DENSITY; DILUTION; FORCE; HYDROGEN BOND; LIQUID; MOLECULAR INTERACTION; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE PROPERTY RELATION; THEORY; THERMODYNAMICS;

EID: 78650201310     PISSN: 18681743     EISSN: 18681751     Source Type: Journal    
DOI: 10.1002/minf.201000027     Document Type: Article

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