QSPR prediction of the solubility of CO2 and N2 in common polymers

Measurement: Journal of the International Measurement Confederation

Volumn 46, Issue 10, 2013, Pages 4206-4225

  Golzar, Karim ^a   Amjad Iranagh, Sepideh ^a   Modarress, Hamid ^a  

^a AMIRKABIR UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Adaptive neuro fuzzy inference system (ANFIS); Artificial neural network (ANN); Genetic function approximation (GFA); Quantitative structure property relationship (QSPR); Solubility

Indexed keywords

CARBON DIOXIDE; FORECASTING; FUZZY SYSTEMS; NEURAL NETWORKS; POLYPROPYLENES; POLYVINYL ACETATES; SOLUBILITY; TRACKING (POSITION);

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM; GENETIC FUNCTION APPROXIMATIONS; NON-LINEAR RELATIONSHIPS; POLY (BUTYLENE SUCCINATE); QUANTITATIVE STRUCTURE PROPERTY RELATIONSHIPS; QUANTITATIVE STRUCTURE-PROPERTY RELATIONSHIP MODELS; SOLUBILITY PREDICTION; TEMPERATURE AND PRESSURES;

POLYMERS;

EID: 84883549810     PISSN: 02632241     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.measurement.2013.08.012     Document Type: Article

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