Volume 12, Number 1 (march 2015 2015)                   IJMSE 2015, 12(1): 12-19 | Back to browse issues page



DOI: 10.22068/ijmse.12.1.12

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Shahbazi B, Rezai B, Chehreh Chelgani S, Koleini S M J, Noaparast M. ESTIMATION OF GAS HOLDUP AND INPUT POWER IN FROTH FLOTATION USING ARTIFICIAL NEURAL NETWORK. IJMSE. 2015; 12 (1) :12-19
URL: http://ijmse.iust.ac.ir/article-1-762-en.html

Abstract:   (1633 Views)
Multivariable regression and artificial neural network procedures were used to modeling of the input power and gas holdup of flotation. The stepwise nonlinear equations have shown greater accuracy than linear ones where they can predict input power, and gas holdup with the correlation coefficients of 0.79 thereby 0.51 in the linear, and R2=0.88 versus 0.52 in the non linear, respectively. For increasing accuracy of predictions, Feed-forward artificial neural network (FANN) was applied. FANNs with 2-2-5-5, and 2-2-3-2-2 arrangements, were capable to estimating of the input power and gas holdup, respectively. They were achieved quite satisfactory correlations of 0.96 in testing stage for input power prediction, and 0.64 for gas holdup prediction
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Type of Study: Research paper | Subject: Ceramics

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