Artificial intelligence-based forecasting model for incinerator in sulfur recovery units to predict SO2 emissions

Pollutant emissions from chemical plants are a major concern in the context of environmental safety. A reliable emission forecasting model can provide important information for optimizing the process and improving the environmental performance. In this work, forecasting models are developed for the...

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Veröffentlicht in:	Environmental research Jg. 249; S. 118329
Hauptverfasser:	Thameem, Muhammed, Raj, Abhijeet, Berrouk, Abdallah, Jaoude, Maguy A., AlHammadi, Ali A.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Inc 15.05.2024
Schlagworte:	Claus process CNN-LSTM Convolutional neural network data collection Emission forecasting environmental performance incinerators Long short-term memory neural networks pollutants prediction sulfur Sulfur recovery unit Claus process Long short-term memory Sulfur recovery unit Convolutional neural network CNN-LSTM Emission forecasting
ISSN:	0013-9351, 1096-0953, 1096-0953
Online-Zugang:	Volltext
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