G. Badalians Gholikandi - Power and Water University of Technology (PWUT), Tehran, Iran, Department of Water and Wastewate Engineering,
N. Karimi - Islamic Azad University-Shahre Rey
M. Ebrahimi - Power and Water University of Technology (PWUT),
H. Hazrati - Sharif University of Technology

The study is to assess dolomite on sludge volume index (SVI) reduction and effluentwastewater quality in aerobic systems by means of artificial neural network. The SBR systemwas undertaken in vessel of 48 L volume and experiments were carried out forcomprehensive investigations. The COD, turbidity and phosphor removal efficiency and SVIreduction were examined through 100 data set collections using artificial neural network. Themost favorable neural network architecture includes 15 neurons along with 1 hidden and 1output layer to adjust inputs correlation efficiently. The result showed the dolomite quantitydepended on MLSS concentration. Also as a result, with increasing dolomite, the CODremoval efficiency increased but the turbidity removal efficiency decreased. Thereforeoptimum dolomite dosage has been determined by standard quality of these parameters.

municipal wastewater treatment, aerobic systems, natural dolomite, artificial neural network (ANN), SVI reduction