Ann-weighted distance grey wolf optimizer for nox emission optimization in coal fired boilers of a thermal power plant

HIGHLIGHTS

  • What: This work seeks to establish the connection between the operating variables and the flue gas NOx emissions through the parametric field experiments. These optimization methods are employed to explore the input space of the neural_network model, aiming to minimize NOx emissions. The aims of boiler combustion optimization are to assist operators in utilizing coal more efficiently and with reduced emissions. The aim of this section is to confirm the effectiveness of the WDGWO algorithm in reducing NOx emissions.
  • Who: Pylarinos from the Abdur Rahman Crescent Institute of Science and Technology, Chennai, India have published . . .

     

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