| 两种数学模型在评判燃煤结渣特性中的改进及应用 |
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| 引用本文： | 文孝强,刘彦臣,孙媛媛,孙灵芳.两种数学模型在评判燃煤结渣特性中的改进及应用[J].东北电力学院学报,2007,27(6):71-76. |
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| 作者姓名： | 文孝强 刘彦臣 孙媛媛 孙灵芳 |
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| 作者单位： | 东北电力大学电力运行仿真中心,吉林,吉林,132012;东北电力大学保卫处,吉林,吉林,132012;东北电力大学自动化工程学院,吉林,吉林,132012 |
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| 摘 要： | 针对常规的模式识别模型和BP网络模型在评判燃煤结渣特性的过程中准确率不高的问题,将两个动态指标引入模型中建立了新的评判模型,通过对几个具体电厂进行评判,结果表明所提出的模型具有较高的评判准确率,从而也证明所提出的模型是合理可行的。
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| 关 键 词： | 模式识别 神经网络 评判 结渣 |
| 文章编号： | 1005-2992（2007）06-0071-06 |
| 收稿时间： | 2007-08-20 |
| 修稿时间： | 2007年8月20日 |
Improvement and Application of Two Mathematics Models in Evaluating the State of Deposition and Slagging of Coal Burning Boiler |
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| WEN Xiao-qiang,LIU Yan-chen,SUN Yuan-yuan,SUN Ling-fang.Improvement and Application of Two Mathematics Models in Evaluating the State of Deposition and Slagging of Coal Burning Boiler[J].Journal of Northeast China Institute of Electric Power Engineering,2007,27(6):71-76. |
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| Authors: | WEN Xiao-qiang LIU Yan-chen SUN Yuan-yuan SUN Ling-fang |
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| Abstract: | To solve the problem of low accuracy of normal pattern-recognition and BP neural-network model in predicting and determining the state of deposition and slagging of coal burning boiler,two dynamic norms are applied in the two new models.Through experiments,it proves that the two new models are higher in accuracy than the traditional ones accordingly and also proves that the models are reasonable and practicable. |
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| Keywords: | Pattern-Recognition Neural-Network Predicting Slagging |
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