Computationally Inexpensive 1D-CNN for the Prediction of Noisy Data of NOx Emissions From 500 MW Coal-Fired Power Plant

Computationally Inexpensive 1D-CNN for the Prediction of Noisy Data of NOx Emissions From 500 MW Coal-Fired Power Plant

Coal-fired power plants have been used to meet the energy requirements in countries where coal reserves are abundant and are the key source of NOx emissions. Owing to the serious environmental and health concerns associated with NOx emissions, much work has been carried out to reduce NOx emissions....

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Autors principals: Muhammad Waqas Saif-Ul-Allah, Javed Khan, Faisal Ahmed, Chaudhary Awais Salman, Zeeshan Gillani, Arif Hussain, Muhammad Yasin, Noaman Ul-Haq, Asad Ullah Khan, Aqeel Ahmed Bazmi, Zubair Ahmad, Mudassir Hasan
Format: Article
Idioma:English
Publicat: Frontiers Media S.A. 2022-08-01
Col·lecció:Frontiers in Energy Research
Matèries:
NOX prediction
machine learning
1D-convolutional neural network
LSTM
GRU
coal-fired power plant
Accés en línia:https://www.frontiersin.org/articles/10.3389/fenrg.2022.945769/full

Internet

https://www.frontiersin.org/articles/10.3389/fenrg.2022.945769/full

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