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Comparative Performance Assessment of Multi Linear Regression and Artificial Neural Network for Prediction of Permeate Flux of Disc Shaped Membrane

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Intelligent Computing & Optimization (ICO 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 569))

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Abstract

Paper compares performance of multi linear regression (MLR) and artificial neural network (ANN) models for predicting permeate flux of disc shaped membrane. To develop the models, permeate flux produced by membrane was considered as model output and parameters like pore size, operating pressure, and feed velocity are considered as model inputs. In the study, model performance index was developed using various statistical parameters like mean square error (MSE), percent bias (PBIAS), Nash-Sutcliffe efficiency (NSE), RMSE-standard deviation of observed data (RSR), and correlation coefficient. It was found that ANN model demonstrate performance index (PI) value of 0.996, whereas MLR model exhibits PI value of 0.003. The high PI demonstrates the accuracy of models. Additionally, it was discovered that, when compared to the MLR model, ANN forecasted values more precisely match the observed data.

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Authors and Affiliations

  1. Department of Civil Engineering, National Institute of Technology Sikkim, Ravangla, South Sikkim, 737139, India

    Anirban Banik

  2. Department of Chemical Engineering, National Institute of Technology Agartala, Jirania, Tripura (W), 799046, India

    Tarun Kanti Bandyopadhyay

  3. Department of Civil Engineering, National Institute of Technology Agartala, Jirania, Tripura (W), 799046, India

    Sushant Kumar Biswal

  4. Russian University of Transport, Obraztsova street, Moscow, 127994, Russia

    Vladimir Panchenko

  5. Federal Scientific Agroengineering Center VIM, 1st Institutsky passage 5, 109428, Moscow, Russia

    Vladimir Panchenko

  6. Department of Civil Engineering, Maharishi Markandeshwar (Deemed to Be University), Mullana, Ambala, Haryana, 133203, India

    Sunil Garhwal

Authors
  1. Anirban Banik
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  2. Tarun Kanti Bandyopadhyay
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  3. Sushant Kumar Biswal
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  4. Vladimir Panchenko
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  5. Sunil Garhwal
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Corresponding author

Correspondence to Anirban Banik .

Editor information

Editors and Affiliations

  1. Modeling Evolutionary Algorithms Simulation and Artificial Intelligence, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Pandian Vasant

  2. Faculty of Engineering Management, Poznan University of Technology, Poznań, Wielkopolskie, Poland

    Gerhard-Wilhelm Weber

  3. Facultad de Ingeniería, Universidad Panamericana, Mexico City, Mexico

    José Antonio Marmolejo-Saucedo

  4. Department of Business Statistics and Operations Research, School of Economic Sciences, North West University, Mahikeng, South Africa

    Elias Munapo

  5. Department of Computer Science, UOW Malaysia KDU Penang University Colle, George Town, Malaysia

    J. Joshua Thomas

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Banik, A., Bandyopadhyay, T.K., Biswal, S.K., Panchenko, V., Garhwal, S. (2023). Comparative Performance Assessment of Multi Linear Regression and Artificial Neural Network for Prediction of Permeate Flux of Disc Shaped Membrane. In: Vasant, P., Weber, GW., Marmolejo-Saucedo, J.A., Munapo, E., Thomas, J.J. (eds) Intelligent Computing & Optimization. ICO 2022. Lecture Notes in Networks and Systems, vol 569. Springer, Cham. https://doi.org/10.1007/978-3-031-19958-5_3

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