Abstract：Taking a 300 MW subcritical circulating fluidized bed boiler as an object of study, the NOx emission of the boiler was predicted accurately. A model about NOx emission from different working conditions was established using hybrid chicken swarm optimization based on simulated annealing(SACSO) and kernel extreme learning machine(KELM). By comparing in the differential evolution algorithm(DE), the particle swarm optimization(PSO) and the original chicken swarm optimization(CSO), the superiority of the improved algorithm was proved. Then, several models were compared in traditional BP algorithm, support vector machine (SVM), extreme learning machine (ELM) and KELM.The Finally determinded SACOS-KELM model has higher prediction accuracy, stability and better generalization ability, so this model is a good choice for boiler NOx emission in modeling and prediction.
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2019, Vol. 40 
