Comparison the capability of artificial neural network (ANN) and EOS for prediction of solid solubilities in supercritical carbon dioxide

Fluid Phase Equilibria

Volumn 308, Issue 1-2, 2011, Pages 35-43

  Lashkarbolooki, M ^a   Vaferi, B ^a   Rahimpour, M R ^a  

^a SHIRAZ UNIVERSITY   (Iran)

Author keywords

Artificial neural network; Cubic equation of state; Mixing rules; Solid solubilities; Supercritical carbon dioxide

Indexed keywords

ARTIFICIAL NEURAL NETWORK; CUBIC EQUATION OF STATE; MIXING RULES; SOLID SOLUBILITIES; SUPERCRITICAL CARBON DIOXIDES;

AROMATIC HYDROCARBONS; AROMATIZATION; BINARY MIXTURES; CARBON DIOXIDE; CARBOXYLIC ACIDS; FORECASTING; MEAN SQUARE ERROR; MIXING; NETWORK LAYERS; NEURAL NETWORKS; OPTIMIZATION; SOLUBILITY; SUPERCRITICAL FLUID EXTRACTION; VAN DER WAALS FORCES;

EQUATIONS OF STATE OF SOLIDS;

EID: 79960714763     PISSN: 03783812     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.fluid.2011.06.002     Document Type: Article

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