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ARTIFICIAL NEURAL NETWORK FOR REMOVAL OF MANGANESE FROM AQUEOUS SOLUTION USING LOW COST ADSORBENT
D. Krishna

Published in: International Journal of Current Engineering And Scientific Research ( IJCESR)
Volume- 4, Issue-11, pp.17-22, Nov 2017
DPI :-> 16.10046.IJCESR.2017.V4I11.1722.2118



Abstract
The objective of the study is to optimize the percentage removal of manganese from waste water using limonia acidissima hull powder as adsorbent with applying artificial neural network (ANN). The effect of various parameters such as pH, adsorbent dosage and initial manganese concentration are investigated to optimize the process parameters and to achieve the maximum percentage removal of manganese ions. Out of total 56 experimental, 40 experimental data points for training and 16 data points for testing have been used by a single layer feed forward back propagation network with 12 neurons to obtain minimum mean square error (MSE) for the development of ANN model. The model was able to find out the percentage removal of manganese efficiently based on regression coefficient value (R2 =0.995).

Key-Words / Index Term
Biosorption, Artificial Neural Network, Limonia acidissima hull powder, Manganese.

How to cite this article
D. Krishna , “ARTIFICIAL NEURAL NETWORK FOR REMOVAL OF MANGANESE FROM AQUEOUS SOLUTION USING LOW COST ADSORBENT”, International Journal of Current Engineering And Scientific Research ( IJCESR), 4, Issue-11, pp.17-22, Nov 2017. DPI:16.10046.IJCESR.V4.I11.2118