NDLI: Artificial Neural Network (ANN) for Optimization of Palm Oil Mill Effluent (POME) Treatment using Reverse Osmosis Membrane

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Artificial Neural Network (ANN) for Optimization of Palm Oil Mill Effluent (POME) Treatment using Reverse Osmosis Membrane

Content Provider	Scilit
Author	Said, Muhammad Ba-Abbad, Muneer Abdullah, Siti Rozaimah Sheik Mohammad, Abdul Wahab
Copyright Year	2018
Description	Journal: Journal of Physics: Conference Series The treatment of palm oil mill effluent (POME) by Reverse Osmosis (RO) membrane was achieved experimentally. The biological oxygen demand (BOD), chemical oxygen demand (COD) and Color as final response of POME treatment process were selected. However, main influence factors on POME treatment process as concentration, transmembrane pressure and pH were tested on responses. The experimental results of responses were compared to the prediction by applying of Artificial Neural Network (ANN) as a simulation technique to create model of the process. Higher validation of ANN model was found for COD, BOD and Color which the prediction values very close compared to experimental result. The COD removal was investigated as a major affect factor in experiments. The best removal of COD was obtained at lower of POME concentration, pH, transmembrane pressure and time of contact. Therefore, these results showed that appreciate model created by ANN for POME treatment process which contributed easily to apply in industrial filed as future application.
Related Links	http://iopscience.iop.org/article/10.1088/1742-6596/1095/1/012021/pdf
ISSN	17426588
e-ISSN	17426596
DOI	10.1088/1742-6596/1095/1/012021
Journal	Journal of Physics: Conference Series
Issue Number	1
Volume Number	1095
Language	English
Publisher	IOP Publishing
Publisher Date	2018-09-01
Access Restriction	Open
Subject Keyword	Journal: Journal of Physics: Conference Series Artificial Neural Network Pome Treatment Process
Content Type	Text
Resource Type	Article
Subject	Physics and Astronomy

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