Water bodies are the most common natural resources that have
been contaminated as a result of different human activities. Actually, in
industries various methods of treatment of wastewater and many adsorbent
materials used for purification of effluents have existed. An artificial neural
network (ANN) was used in this study to predict the removal of sodium
decanesulfonate using actived carbon obtained by the calcination of mineral
biomass under different conditions. The structure of [3-3-1] was obtained and given
a good correlation coefficient (R2 = 0.9965) with root mean squared error (RMSE
= 0.0276). For the stage of interpolation and extrapolation, the results
present a high correlation coefficient close to 1 which provides the robustness
and the high capacity of ANN developed model.
Author(s)details:-
Sediri Meriem
Biomaterials and Transport Phenomena Laboratory (LBMPT), University of
Médéa, 26000, Médéa, Algeria.
Hanini Salah
Biomaterials and Transport Phenomena Laboratory (LBMPT), University of
Médéa, 26000, Médéa, Algeria.
Please See the book
here :- https://doi.org/10.9734/bpi/caert/v10/2974
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