Enhancing Effluent Quality Predictions in Wastewater Treatment with LSTM Neural Network

This research paper delves into the application of Long Short-Term Memory (LSTM) neural networks within the Benchmark Simulation Model No. 2 (BSM2) to enhance the predictability and efficiency of wastewater treatment processes. The study aims to develop advanced predictive models that can simulate t...

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Veröffentlicht in:	International Conference on System Theory, Control and Computing S. 83 - 88
Hauptverfasser:	Voipan, Daniel, Vasiliev, Iulian, Diaconu, Larisa, Voipan, Andreea-Elena, Barbu, Marian
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 10.10.2024
Schlagworte:	Accuracy Adaptation models Artificial Neural Networks BSM2 Effluent Quality Effluents Long short term memory LSTM Predictive models Real-time systems Stochastic processes Time series analysis Wastewater Wastewater treatment Wastewater Treatment Plants
ISSN:	2473-5698
Online-Zugang:	Volltext
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