Enhanced Performance of Wastewater Membrane Bioreactor Using Machine Learning Model’s Prediction and Optimization
This study aimed to enhance wastewater treatment at the Yongkang Water Resource Recovery Center by integrating mechanistic modeling results into machine learning (ML). We combined IoT sensor data from treatment processes with the mechanistic modeling results to develop a hybrid model using ML method...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
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| Series: | Engineering Proceedings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-4591/91/1/4 |
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| Summary: | This study aimed to enhance wastewater treatment at the Yongkang Water Resource Recovery Center by integrating mechanistic modeling results into machine learning (ML). We combined IoT sensor data from treatment processes with the mechanistic modeling results to develop a hybrid model using ML methods for predicting effluent quality, specifically focusing on chemical oxygen demand. The developed hybrid model offers advantages in the evaluation of the Theil inequality coefficient, mean absolute error, and coefficient of variation and addresses the convergence issues encountered in ML models with IoT sensor data. Guidance provided by the model mitigates the challenges associated with poor-quality IoT data. |
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| ISSN: | 2673-4591 |