QSPR molecular approach for representation/prediction of very large vapor pressure dataset

Chemical Engineering Science

Volumn 76, Issue , 2012, Pages 99-107

  Gharagheizi, Farhad ^a   Eslamimanesh, Ali ^b   Ilani Kashkouli, Poorandokht ^a   Mohammadi, Amir H ^b,c   Richon, Dominique ^b,c  

^a ISLAMIC AZAD UNIVERSITY   (Iran)

^b PSL RESEARCH UNIVERSITY   (France)

^c UNIVERSITY OF KWAZULU NATAL   (South Africa)

Author keywords

Computational chemistry; Optimization; Phase equilibria; Quantitative structure property relationship; Thermodynamics process; Vapor pressure

Indexed keywords

APPROPRIATE MODELS; DATA SETS; LARGE DATA; LEVENBERG-MARQUARDT; MATHEMATICAL METHOD; MOLECULAR APPROACH; MOLECULAR DESCRIPTORS; OPTIMIZATION STRATEGY; PREDICTIVE MODELS; PRESSURE VALUES; QSPR MODEL; QUANTITATIVE STRUCTURE PROPERTY RELATIONSHIPS; RELATIVE DEVIATIONS; SEARCH METHOD; SEQUENTIAL SEARCH; SQUARED CORRELATION COEFFICIENTS; THREE-LAYER; VALUE STATISTICS;

CHEMICAL COMPOUNDS; CHEMICAL INDUSTRY; COMPUTATIONAL CHEMISTRY; NEURAL NETWORKS; OPTIMIZATION; PHASE EQUILIBRIA; THERMODYNAMICS; VAPOR PRESSURE; VAPORS;

HYDROSTATIC PRESSURE;

EID: 84860335530     PISSN: 00092509     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ces.2012.03.033     Document Type: Article

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