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- W4211040367 abstract "The chapter demonstrates the application of neural network–based group method of data handling (GMDH) for prediction of permeate flux (%) in disc-shaped membrane. The permeate flux is predicted using three parameters for this study, like pore size, operating pressure, and feed velocity. Different statistical techniques such as mean absolute error, root mean square error (RMSE), RMSE-observation standard deviation error, and Pearson's correlation coefficient are analyzed in order to show the precision of the GMDH-NN models. To demonstrate the performance of GMDH-NN model, the total error values are compared with the developed artificial neural network model. It was found that total error value of GMDH-NN and ANN model are 0.74 and 0.91, respectively. The study illustrates that GMDH model predicts permeate flux of disc membrane with high accuracy." @default.
- W4211040367 created "2022-02-13" @default.
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- W4211040367 date "2022-02-11" @default.
- W4211040367 modified "2023-10-12" @default.
- W4211040367 title "Application of Group Method of Data Handling–Based Neural Network (GMDH‐NN) for Forecasting Permeate Flux (%) of Disc‐Shaped Membrane" @default.
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- W4211040367 doi "https://doi.org/10.1002/9781119792642.ch7" @default.
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