Abstract：As to precisely predict the NOx emission from boiler,an integrated modeling method was establisbcd based on gravitation search algorithm (GSA) and parallel extreme learning machine (PELM),and used the model to forecast the power plant boiler NOx emission concentration.As the generalization ability and accuracy of PELM rely on the choice of weight,using the gravitation search algorithm optimization PELM weights.Test sample data were collected in a coal-fired power plant 300 MW circulating fluidized bed boiler under different conditions,the simulation consequences showed that compared with PELM model,ELM model,GSA-LSSVM and GSA-ELM model,GSA-PELM model the accuracy could be improved by more than 9 orders of magnitude and can be used more effectively and accurately to predict NOx emission concentration of boilers in thermal power plants.
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2018, Vol. 39 
