Prediction of surface tension of pure hydrocarbons by an artificial neural network system

Petroleum Science and Technology

Volumn 29, Issue 22, 2011, Pages 2384-2396

  Pazuki, G R ^a   Nikookar, M ^b   Sahranavard, L ^b  

^a AMIRKABIR UNIVERSITY OF TECHNOLOGY   (Iran)

^b NATIONAL IRANIAN OIL COMPANY   (Iran)

Author keywords

neural network modeling; parachor constant; surface tension

Indexed keywords

ARTIFICIAL NEURAL NETWORK; EQUATION OF STATE; EXPERIMENTAL DATA; LEARNING METHODS; MULTI-LAYER PERCEPTRON NEURAL NETWORKS; NEURAL NETWORK MODELING; PARACHOR CONSTANT; PURE HYDROCARBONS; ROOT MEAN SQUARE ERRORS; STATISTICAL CRITERION; THREE-LAYER;

BACKPROPAGATION; EQUATIONS OF STATE; HYDROCARBONS; MEAN SQUARE ERROR; SURFACE TENSION;

NEURAL NETWORKS;

EID: 80053251301     PISSN: 10916466     EISSN: 15322459     Source Type: Journal    
DOI: 10.1080/10916461003735020     Document Type: Article

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