Abstract
In the concerned research, the Group method of data handling (GMDH) algorithm has been used to predict the efficiency of the vertical helical coil membrane. Parameters such as inlet pressure (kPa), inlet velocity (m/sec) and pore size (µm) of the membrane have been selected as the input parameters of the model, whereas the efficiency of the membrane has been considered as the output of the model for prediction purpose. The acceptability of the developed model is evaluated by using model evaluation parameters like Nash-Sutcliffe efficiency (NSE), the ratio of the root mean squared error to the standard deviation (RSR), Percent bias (PBIAS) etc. GMDH has also been used as an optimization technique for optimizing the operating parameters of the vertical helical coil membrane. It has been found that when the pressure across the membrane is 1.03 × 10−05 kPa, the inlet velocity of the membrane is 36.69 cm/sec and pore size is 2.21 µm then membrane exhibits maximum efficiency and minimum fouling tendency. A comparative error analysis has been also carried out between the developed model in GMDH, and MLR techniques and it has been found that the GMDH model contains minimum error percentages compared to the other model. The above study can be used for developing and designing the membrane with improved anti-fouling property.
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Banik, A., Bandyopadhyay, T.K., Biswal, S.K., Majumder, M. (2020). Prediction of Maximum Efficiency of Vertical Helical Coil Membrane Using Group Method of Data Handling (GMDH) Algorithm. In: Vasant, P., Zelinka, I., Weber, GW. (eds) Intelligent Computing and Optimization. ICO 2019. Advances in Intelligent Systems and Computing, vol 1072. Springer, Cham. https://doi.org/10.1007/978-3-030-33585-4_48
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