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Prediction of NOx Emission of Boiler Based on Improved Optimal Foraging Algorithm |
NIU Pei-feng,PENG Peng |
School of Electrical Engineering, Yanshan University, Qinhuangdao, Hebei 066004, China |
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Abstract An improved optimal foraging algorithm is proposed, the update direction of adaptive inertia weight and global optimal solution is introduced in the optimal foraging algorithm, at the same time, the mechanism of phase space search is introduced. The improved optimal foraging algorithm (POFA) optimized by extreme learning machine (ELM) constructs an improved extreme learning machine model (POFA-ELM) and uses the POFA-ELM model to model the boiler NOx emission characteristics.Compared with ELM and differential evolution algorithm, particle swarm optimization, artificial bee colony algorithm, and basic optimal foraging algorithm optimized ELM model, the results show that the POFA-ELM model has better prediction accuracy and stronger generalization ability, which can predict the NOx emission quality concentration more accurately.
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Received: 25 September 2018
Published: 29 June 2020
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