Iranian Journal of Materials Science and Engineering
Iran University of Science & Technology
Wed, Jul 17, 2024
[Archive]
Volume 12, Issue 1 (march 2015 2015)
IJMSE 2015, 12(1): 12-19 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
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
URL: http://ijmse.iust.ac.ir/article-1-762-en.html
Abstract: (15127 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
Type of Study: Research Paper |
Subject:
Ceramics
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
