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M. Sadeghi1 , M. Kazemimoghadam2 , R. Khalilzadeh3
Section:Research Paper, Product Type: Journal-Paper
Vol.10 ,
Issue.5 , pp.9-15, Oct-2023
Online published on Oct 31, 2023
Copyright © M. Sadeghi, M. Kazemimoghadam, R. Khalilzadeh . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: M. Sadeghi, M. Kazemimoghadam, R. Khalilzadeh, “Neural Network Modeling for The Microfiltration Process of Bacteria Harvesting From Fermentation Liquid,” International Journal of Scientific Research in Chemical Sciences, Vol.10, Issue.5, pp.9-15, 2023.
MLA Style Citation: M. Sadeghi, M. Kazemimoghadam, R. Khalilzadeh "Neural Network Modeling for The Microfiltration Process of Bacteria Harvesting From Fermentation Liquid." International Journal of Scientific Research in Chemical Sciences 10.5 (2023): 9-15.
APA Style Citation: M. Sadeghi, M. Kazemimoghadam, R. Khalilzadeh, (2023). Neural Network Modeling for The Microfiltration Process of Bacteria Harvesting From Fermentation Liquid. International Journal of Scientific Research in Chemical Sciences, 10(5), 9-15.
BibTex Style Citation:
@article{Sadeghi_2023,
author = {M. Sadeghi, M. Kazemimoghadam, R. Khalilzadeh},
title = {Neural Network Modeling for The Microfiltration Process of Bacteria Harvesting From Fermentation Liquid},
journal = {International Journal of Scientific Research in Chemical Sciences},
issue_date = {10 2023},
volume = {10},
Issue = {5},
month = {10},
year = {2023},
issn = {2347-2693},
pages = {9-15},
url = {https://www.isroset.org/journal/IJSRCS/full_paper_view.php?paper_id=3298},
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
UR - https://www.isroset.org/journal/IJSRCS/full_paper_view.php?paper_id=3298
TI - Neural Network Modeling for The Microfiltration Process of Bacteria Harvesting From Fermentation Liquid
T2 - International Journal of Scientific Research in Chemical Sciences
AU - M. Sadeghi, M. Kazemimoghadam, R. Khalilzadeh
PY - 2023
DA - 2023/10/31
PB - IJCSE, Indore, INDIA
SP - 9-15
IS - 5
VL - 10
SN - 2347-2693
ER -
Abstract :
Microfiltration is considered useful processes in the field of food industry separation. In the present study, neural network modeling for laboratory data was performed using a ceramic microfiltration membrane to isolate Kocuria rhizophila bacteria from the feed stream. The independent parameters of this process are the back pressure of the membrane, speed of the current entering the membrane, contact time, and the dependent parameter of the flux passing through the membrane. The neural network used was a multilayer perceptron (MLP) system. The data are divided into three main parts of education, validation, and evaluation with a distribution percentage of 15-15-70. The variable of the number of hidden layer neurons in this study was changed from 1 to 20, and the value of 17 neurons was selected as the optimal number according to the results. for verify the prediction performance of the data in the neural network, two basic parameters of the determination coefficient (R2, mean square error (MSE)) were used. The R2 values for the training data, validation, evaluation, and all data using the learning function and the optimal transfer function of Levenberg-Marquardt and Tansing were 0.9995, 0.99966, 0.999111, and 0.9994, respectively. In addition, an MSE value of 0.008 was obtained, indicating a very low error rate. The results show that the neural network used and the optimal function obtained had the least errors in the data calculations and predictions.
Key-Words / Index Term :
neural network - microfiltration - bacteria - MLP
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