Modelling of the batch sucrose crystallization kinetics using artificial neural networks: Comparison with conventional regression analysis

Industrial and Engineering Chemistry Research

Volumn 47, Issue 14, 2008, Pages 4917-4923

  Vasanth Kumar, K ^a   Martins, P ^b   Rocha, F ^a  

^a UNIVERSITY OF PORTO   (Portugal)

^b UNIVERSITY OF PORTO   (Portugal)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BACKPROPAGATION; CORRELATION METHODS; CRYSTAL GROWTH; CRYSTALLIZATION; CRYSTALLIZATION KINETICS; ECOLOGY; FISCHER-TROPSCH SYNTHESIS; FOOD PROCESSING; FORECASTING; GRAIN BOUNDARIES; GROWTH RATE; IMAGE CLASSIFICATION; POWDERS; REGRESSION ANALYSIS; SUGAR (SUCROSE); VEGETATION;

AGITATION SPEEDS; ARTIFICIAL NEURAL NETWORK; ARTIFICIAL NEURAL NETWORKS; CORRELATION CO-EFFICIENT; CRYSTAL GROWTH RATES; DIFFERENT OPERATING CONDITIONS; FEED-FORWARD; INPUT DATA; MULTIPLE NON LINEAR REGRESSIONS; NONLINEAR REGRESSION ANALYSIS; OPERATING CONDITIONS; OPERATING VARIABLES; SEED CRYSTALS;

NEURAL NETWORKS;

EID: 49249115556     PISSN: 08885885     EISSN: None     Source Type: Journal    
DOI: 10.1021/ie701706v     Document Type: Article

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