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Volume 17
Issue 20
10.3390/w17203003
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Hybrid RSM–ANN Modeling for Optimization of Electrocoagulation Using Aluminum Electrodes (Al–Al) for Hospital Wastewater Treatment

by
Khanit Matra
1,
Yanika Lerkmahalikit
2,
Sirilak Prasertkulsak
3,
Amnuaychai Kongdee
4,
Raweeporn Pomthong
5,
Suchira Thongson
5 and
Suthida Theepharaksapan
5,6,*
1
Department of Electrical Engineering, Engineering Faculty, Srinakharinwirot University, Ongkharak, Nakhon Nayok 26120, Thailand
2
Central Instruments Center Building, Excellent Center Sustainable, Engineering Faculty, Srinakharinwirot University, Ongkharak, Nakhon Nayok 26120, Thailand
3
Department of Environmental Engineering, Faculty of Engineering and Architecture, Rajamangala University of Technology Suvarnabhumi, Phra Nakhon Si Ayutthaya, Ayutthaya 13000, Thailand
4
Royal Irrigation Department, Dusit, Bangkok 10300, Thailand
5
Department of Civil and Environmental Engineering, Engineering Faculty, Srinakharinwirot University, Ongkharak, Nakhon Nayok 26120, Thailand
6
Center of Excellence in Rail System Technology and Civil Engineering Material Innovation for Sustainable Infrastructure, Strategic Wisdom and Research Institute, Srinakharinwirot University, Watthana, Bangkok 10110, Thailand
*
Author to whom correspondence should be addressed.
Water 2025, 17(20), 3003; https://doi.org/10.3390/w17203003 (registering DOI)
Submission received: 17 September 2025 / Revised: 15 October 2025 / Accepted: 17 October 2025 / Published: 18 October 2025
(This article belongs to the Special Issue Advanced Treatment Technologies for Emerging Contaminants in Wastewater)
Versions Notes

Abstract

Electrocoagulation (EC) employing aluminum–aluminum (Al–Al) electrodes was investigated for hospital wastewater treatment, targeting the removal of turbidity, soluble chemical oxygen demand (sCOD), and total dissolved solids (TDS). A hybrid modeling framework integrating response surface methodology (RSM) and artificial neural networks (ANN) was developed to enhance predictive reliability and identify energy-efficient operating conditions. A Box–Behnken design with 15 experimental runs evaluated the effects of pH, current density, and electrolysis time. Multi-response optimization determined the overall optimal conditions at pH 7.0, current density 20 mA/cm2, and electrolysis time 75 min, achieving 94.5% turbidity, 69.8% sCOD, and 19.1% TDS removal with a low energy consumption of 0.34 kWh/m3. The hybrid RSM–ANN model exhibited high predictive accuracy (R2 > 97%), outperforming standalone RSM models, with ANN more effectively capturing nonlinear relationships, particularly for TDS. The results confirm that EC with Al–Al electrodes represent a technically promising and energy-efficient approach for decentralized hospital wastewater treatment, and that the hybrid modeling framework provides a reliable optimization and prediction tool to support process scale-up and sustainable water reuse.
Keywords: hospital wastewater; electrocoagulation (EC); wastewater treatment; response surface methodology (RSM); artificial neural network (ANN) hospital wastewater; electrocoagulation (EC); wastewater treatment; response surface methodology (RSM); artificial neural network (ANN)

Share and Cite

MDPI and ACS Style

Matra, K.; Lerkmahalikit, Y.; Prasertkulsak, S.; Kongdee, A.; Pomthong, R.; Thongson, S.; Theepharaksapan, S. Hybrid RSM–ANN Modeling for Optimization of Electrocoagulation Using Aluminum Electrodes (Al–Al) for Hospital Wastewater Treatment. Water 2025, 17, 3003. https://doi.org/10.3390/w17203003

AMA Style

Matra K, Lerkmahalikit Y, Prasertkulsak S, Kongdee A, Pomthong R, Thongson S, Theepharaksapan S. Hybrid RSM–ANN Modeling for Optimization of Electrocoagulation Using Aluminum Electrodes (Al–Al) for Hospital Wastewater Treatment. Water. 2025; 17(20):3003. https://doi.org/10.3390/w17203003

Chicago/Turabian Style

Matra, Khanit, Yanika Lerkmahalikit, Sirilak Prasertkulsak, Amnuaychai Kongdee, Raweeporn Pomthong, Suchira Thongson, and Suthida Theepharaksapan. 2025. "Hybrid RSM–ANN Modeling for Optimization of Electrocoagulation Using Aluminum Electrodes (Al–Al) for Hospital Wastewater Treatment" Water 17, no. 20: 3003. https://doi.org/10.3390/w17203003

APA Style

Matra, K., Lerkmahalikit, Y., Prasertkulsak, S., Kongdee, A., Pomthong, R., Thongson, S., & Theepharaksapan, S. (2025). Hybrid RSM–ANN Modeling for Optimization of Electrocoagulation Using Aluminum Electrodes (Al–Al) for Hospital Wastewater Treatment. Water, 17(20), 3003. https://doi.org/10.3390/w17203003

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