Iranian Journal of Materials Science & Engineering
Iranian Journal of Materials Science & Engineering
IJMSE
Engineering & Technology
http://ijmse.iust.ac.ir
18
agent2
1735-0808
2383-3882
10.22068/ijmse
en
jalali
1393
12
1
gregorian
2015
3
1
12
1
online
1
fulltext
en
ESTIMATION OF GAS HOLDUP AND INPUT POWER IN FROTH FLOTATION USING ARTIFICIAL NEURAL NETWORK
گروه سرامیک
Ceramics
Research paper
Research paper
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
Flotation, Input Power, Gas Holdup, Regression, Artificial Neural Network
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19
http://ijmse.iust.ac.ir/browse.php?a_code=A-10-127-71&slc_lang=en&sid=1
B.
Shahbazi
`180031947532846003001`

180031947532846003001
Yes
B.
Rezai
`180031947532846003002`

180031947532846003002
No
S.
Chehreh Chelgani
`180031947532846003003`

180031947532846003003
No
S. M. J.
Koleini
`180031947532846003004`

180031947532846003004
No
M.
Noaparast
`180031947532846003005`

180031947532846003005
No