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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Bibliographic Details
Main Authors: 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
Language:English
Published: Frontiers Media S.A. 2022-08-01
Series:Frontiers in Energy Research
Subjects:
NOX prediction
machine learning
1D-convolutional neural network
LSTM
GRU
coal-fired power plant
Online Access: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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