Publications by authors named "Kangrong Tang"
J Environ Manage
December 2024
Article Synopsis
- This study explores the integration of deep learning, specifically LSTM networks, in managing aeration systems for wastewater treatment to enhance operational sustainability.*
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- It compares two ensemble learning algorithms, AdaBoost and Bagging, focusing on their effectiveness in predicting aeration status through one-step and multi-step forecasts, particularly under extreme circumstances like sudden ammonia spikes.*
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- Results show that AdaBoost-LSTM models outperform Bagging-LSTM models, especially in multi-step predictions, achieving higher precision and ensuring stable aeration, ultimately leading to significant energy savings and improved system performance.*
