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Optimal Parameter Determination of Membrane Bioreactor to Boost Biohydrogen Production-Based Integration of ANFIS Modeling and Honey Badger Algorithm

Author

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  • Hegazy Rezk

    (Department of Electrical Engineering, College of Engineering in Wadi Alddawasir, Prince Sattam bin Abdulaziz University, Wadi Alddawasir 11991, Saudi Arabia)

  • A. G. Olabi

    (Sustainable Energy & Power Systems Research Centre, RISE, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates)

  • Mohammad Ali Abdelkareem

    (Sustainable Energy & Power Systems Research Centre, RISE, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates
    Faculty of Engineering, Minia University, Minia 61111, Egypt)

  • Abdul Hai Alami

    (Sustainable Energy & Power Systems Research Centre, RISE, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates)

  • Enas Taha Sayed

    (Faculty of Engineering, Minia University, Minia 61111, Egypt)

Abstract

Hydrogen is a new promising energy source. Three operating parameters, including inlet gas flow rate, pH and impeller speed, mainly determine the biohydrogen production from membrane bioreactor. The work aims to boost biohydrogen production by determining the optimal values of the control parameters. The proposed methodology contains two parts: modeling and parameter estimation. A robust ANIFS model to simulate a membrane bioreactor has been constructed for the modeling stage. Compared with RMS, thanks to ANFIS, the RMSE decreased from 2.89 using ANOVA to 0.0183 using ANFIS. Capturing the proper correlation between the inputs and output of the membrane bioreactor process system encourages the constructed ANFIS model to predict the output performance exactly. Then, the optimal operating parameters were identified using the honey badger algorithm. During the optimization process, inlet gas flow rate, pH and impeller speed are used as decision variables, whereas the biohydrogen production is the objective function required to be maximum. The integration between ANFIS and HBA boosted the hydrogen production yield from 23.8 L to 25.52 L, increasing by 7.22%.

Suggested Citation

  • Hegazy Rezk & A. G. Olabi & Mohammad Ali Abdelkareem & Abdul Hai Alami & Enas Taha Sayed, 2023. "Optimal Parameter Determination of Membrane Bioreactor to Boost Biohydrogen Production-Based Integration of ANFIS Modeling and Honey Badger Algorithm," Sustainability, MDPI, vol. 15(2), pages 1-13, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:2:p:1589-:d:1035130
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    References listed on IDEAS

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    Cited by:

    1. Hegazy Rezk & Abdul Ghani Olabi & Enas Taha Sayed & Samah Ibrahim Alshathri & Mohammad Ali Abdelkareem, 2023. "Optimized Artificial Intelligent Model to Boost the Efficiency of Saline Wastewater Treatment Based on Hunger Games Search Algorithm and ANFIS," Sustainability, MDPI, vol. 15(5), pages 1-16, March.

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