Neural network based prediction and optimization of NO<sub>x</sub> emission from coal-fired boilers

YU Tingfang; LI Penghui

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Neural network based prediction and optimization of NO_x emission from coal-fired boilers

Thermal Power Generation Vol. 44, Issue 4, Pages: 112-115(2015)

更新时间：2025-09-28

- Neural network based prediction and optimization of NO_x emission from coal-fired boilers
- 作者机构：
  
  南昌大学机电工程学院
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP18;TM621.2
- Published：2015
- 稿件说明：
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YU Tingfang, LI Penghui. Neural network based prediction and optimization of NO_x emission from coal-fired boilers[J]. Thermal Power Generation, 2015, 44(4): 112-115.
DOI：

YU Tingfang, LI Penghui. Neural network based prediction and optimization of NO_x emission from coal-fired boilers[J]. Thermal Power Generation, 2015, 44(4): 112-115. DOI：

摘要

应用Matlab神经网络工具箱对某燃煤电站锅炉NOx排放特性进行神经网络建模。仿真结果表明

该模型具有良好的准确性和泛化能力

模型平均相对误差为1.37%

具有较高的准确性。基于该NOx排放预测模型

结合遗传算法对燃煤锅炉的NOx排放进行优化

按照优化结果推荐的运行参数

在相同的运行负荷工况下

其NOx排放浓度由优化前的456.2mg/m3降为323.9mg/m3

下降幅度达到了29%

效果显著。

Abstract

The Matlab neural network toolbox was applied to establish the prediction model for NOxemission in a coal-fired power plant boiler.The simulation results show that this forecast model has well accuracy and generalization ability

its average relative error is 1.37%

which means the high accuracy.On the basis of this NOxemission prediction model

the NOxemission was optimized by genetic algorithm.According to the recommended operating parameters

after the optimization

the NOxemission decreased from 456.2mg/m3 to 323.9mg/m3 under the same operation load conditions

reduced by 29%

which is dramatic.

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Neural network based prediction and optimization of NOx emission from coal-fired boilers

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摘要

Abstract

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Neural network based prediction and optimization of NO_x emission from coal-fired boilers