Artificial intelligence-based forecasting model for incinerator in sulfur recovery units to predict SO2 emissions-Reference-Cited by-同舟云学术

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

Published:2024-05 Issue: Volume:249 Page:118329
ISSN:0013-9351
Container-title:Environmental Research
language:en
Short-container-title:Environmental Research

Author:

Thameem Muhammed,Raj Abhijeet,Berrouk Abdallah^ORCID,Jaoude Maguy A.^ORCID,AlHammadi Ali A.^ORCID

Funder

Khalifa University of Science, Technology and Research

Publisher

Elsevier BV

Reference32 articles.

1. Software sensor for sulphur recovery unit control;Bolf;Chem Eng Trans,2009

2. Orthogonal least squares algorithm for training multi-output radial basis function networks;Chen,1991

3. Gated feedback recurrent neural networks;Chung,2015

4. Air Quality and Stationary Source Emission Control,1974

5. RNN- and LSTM-based soft sensors transferability for an industrial process;Curreri;Sensors,2021

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Eco-friendly nanotechnology in rheumatoid arthritis: ANFIS-XGBoost enhanced layered nanomaterials;Environmental Research;2024-12

2. Leveraging long short‐term memory networks and transfer learning for the soft‐measurement of flue gas flowrate from coal‐fired boilers;Asia-Pacific Journal of Chemical Engineering;2024-08-19

3. Machine Learning-Enabled Prediction and Optimization of Sulfur Recovery Units: A Step towards Industry 4.0 Integration;CEMP 2023;2024-04-07

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