摘要
本文提出了基于BP神经网络算法的电厂锅炉燃烧系统模型,经过对燃烧系统模型的验证说明了此模型的可行性。在此基础上提出了基于粒子群(PSO)算法的燃烧系统寻优模型,分别对锅炉的NO_x排放量,锅炉效率和兼顾NO_x排放量、锅炉效率的优化计算,表明寻优模型可取得较好的优化效果。
This paper presents BP neural network algorithm for Power plant boiler combustion system model, After verification of the model of the combustion system, The feasibility of the model is proved. Based on this model Particle swarm optimization （PSO） algorithm is proposed for Combustion system optimization model, Respectively Boiler NOx emissions, Boiler efficiency, Both NOx emissions and Boiler efficiency to Optimization calculation, The results show that the model can achieve good results.
出处
《锅炉制造》
2016年第4期30-33,共4页
Boiler Manufacturing
关键词
燃烧优化
BP神经网络
粒子群算法
Combustion optimization
BP neural network
Particle swarm optimization algorithm
