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Membrane Water Treatment   Volume 9, Number 2, March 2018, pages 115-121
Modelling of starch industry wastewater microfiltration parameters by neural network
Aleksandar I. Jokić, Laslo L. Šereš, Nemanja R. Milović, Zita I. Šereš, Nikola R. Maravić, Žana Šaranović and Ljubica P. Dokić

Abstract     [Buy Article]
    Artificial neural network (ANN) simulation is used to predict the dynamic change of permeate flux during wheat starch industry wastewater microfiltration with and without static turbulence promoter. The experimental program spans range of a sedimentation times from 2 to 4 h, for feed flow rates 50 to 150 L/h, at transmembrane pressures covering the range of 1x10^5 to 3x10^5 Pa. ANN predictions of the wastewater microfiltration are compared with experimental results obtained using two different set of microfiltration experiments, with and without static turbulence promoter. The effects of the training algorithm, neural network architectures on the ANN performance are discussed. For the most of the cases considered, the ANN proved to be an adequate interpolation tool, where an excellent prediction was obtained using automated Bayesian regularization as training algorithm. The optimal ANN architecture was determined as 4-10-1 with hyperbolic tangent sigmoid transfer function transfer function for hidden and output layers. The error distributions of data revealed that experimental results are in very good agreement with computed ones with only 2% data points had absolute relative error greater than 20% for the microfiltration without static turbulence promoter whereas for the microfiltration with static turbulence promoter it was 1%. The contribution of filtration time variable to flux values provided by ANNs was determined in an important level at the range of 52-66% due to increased membrane fouling by the time. In the case of microfiltration with static turbulence promoter, relative importance of transmembrane pressure and feed flow rate increased for about 30%.
Key Words
    wheat starch industry wastewater; microfiltration; artificial neural networks
Aleksandar I. Jokić,Nemanja R. Milović, Zita I. Šereš, Nikola R. Maravić and Ljubica P. Dokić: University of Novi Sad, Faculty of Technology, Bul. cara Lazara 1, 21000 Novi Sad, Serbia

Laslo L. Šereš: University of Novi Sad, Faculty of Economics in Subotica, Segedinski put 9-11, 24000 Subotica, Serbia

Žana Šaranović: Institute of Economics ad, Ulica Kralja Milana 16, 11000 Belgrade, Serbia, AD Fidelinka, Fidelinka – Starch, Čantavirski put 1, 24000 Subotica, Serbia

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