Optimization of ultrasound-assisted base-catalyzed methanolysis of sunflower oil using response surface and artifical neural network methodologies

Chemical Engineering Journal

Volumn 215-216, Issue , 2013, Pages 82-89

  Rajković, Katarina M ^a   Avramović, Jelena M ^b   Milić, Petar S ^a   Stamenković, Olivera S ^b   Veljković, Vlada B ^b  

^a High Chemical and Technological School for Professional Studies   (Serbia)

^b UNIVERSITY OF NI   (Serbia)

Author keywords

Artificial neural network; Biodiesel; Methanolysis; Response surface methodology; Sunflower oil; Ultrasound

Indexed keywords

ANN PREDICTION; ARTIFICAL NEURAL NETWORKS; BACK PROPAGATION ARTIFICIAL NEURAL NETWORK (BPANN); CATALYST LOADINGS; FULL FACTORIAL DESIGN; GENERALIZATION ABILITY; INITIAL METHANOL; INPUT FACTORS; METHANOLYSIS; METHANOLYSIS PROCESS; MOLAR RATIO; OPERATIONAL VARIABLES; OPTIMIZATION STUDIES; OUTPUT RESPONSE; PROCESS FACTOR; REACTION TEMPERATURE; RESPONSE SURFACE; RESPONSE SURFACE METHODOLOGY; SECOND-ORDER POLYNOMIAL EQUATIONS; SUNFLOWER OIL; ULTRA-SONICATION;

BIODIESEL; CATALYSIS; CATALYSTS; DESIGN OF EXPERIMENTS; FORECASTING; NEURAL NETWORKS; OPTIMIZATION; POLYNOMIALS; SURFACE PROPERTIES; ULTRASONICS; VEGETABLE OILS;

LOADING;

HELIANTHUS;

EID: 84870192605     PISSN: 13858947     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cej.2012.10.069     Document Type: Article

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