NOx emission prediction for coal-fired boilers based on RBF Neural network and BP Neural network

YU Tingfang; LIU Ran

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NOx emission prediction for coal-fired boilers based on RBF Neural network and BP Neural network

Thermal Power Generation Issue 7, (2016)

更新时间：2025-09-28

- NOx emission prediction for coal-fired boilers based on RBF Neural network and BP Neural network
- 作者机构：
  
  南昌大学机电工程学院,江西,南昌,330031
- 作者简介：
- 基金信息：
- DOI：
  CLC： TK223.23
- Published Online：15 August 2016，
  
  Published：2016
- 稿件说明：
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YU Tingfang, LIU Ran. NOx emission prediction for coal-fired boilers based on RBF Neural network and BP Neural network[J]. Thermal Power Generation, 2016, (7).
DOI：

YU Tingfang, LIU Ran. NOx emission prediction for coal-fired boilers based on RBF Neural network and BP Neural network[J]. Thermal Power Generation, 2016, (7). DOI：

摘要

基于某超超临界660 MW机组燃煤锅炉现场热态实验数据

利用MATLAB智能工具箱

分别采用径向基(RBF)神经网络和BP神经网络对该锅炉NOx排放特性进行建模

采用交替梯度算法对RBF神经网络预测模型进行输出层权值及RBF函数的中心与标准偏差值优化

对BP神经网络采用动量法进行改进。2种模型的仿真和预测结果对比分析表明:参数优化后的RBF神经网络预测模型预测结果的最大误差为3.0％

平均误差为1.75％；改进后的BP神经网络预测模型预测结果最大误差为6.6％

平均误差为4.5％；2种建模方法均具有较好的准确性和泛化能力

其中RBF神经网络模型的计算速度快，拟合和泛化能力更强。

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