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


XML Print


Download citation:
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
Abstract:   (14655 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
Full-Text [PDF 6512 kb]   (4384 Downloads)    
Type of Study: Research Paper | Subject: Ceramics

Add your comments about this article : Your username or Email:
CAPTCHA

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2022 All Rights Reserved | Iranian Journal of Materials Science and Engineering

Designed & Developed by : Yektaweb