| 混煤硫释放的BP神经网络模型预测 |
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| 引用本文： | 尉庆国,刘汉涛,苏铁熊.混煤硫释放的BP神经网络模型预测[J].煤炭转化,2010,33(2). |
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| 作者姓名： | 尉庆国 刘汉涛 苏铁熊 |
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| 作者单位： | 中北大学机电工程学院,030001,太原 |
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| 基金项目： | 山西省青年创新基金资助项目(200821004) |
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| 摘 要： | 通过对不同混煤一维燃烧过程中H2S和SO2释放特性的有关数据,应用BP人工神经网络进行预测.通过分析和计算建立了典型的三层BP网络,输入神经元为8个,隐含层神经元个数为6个,输出层神经元个数为2个,用加入动量项的方法对传统的BP网络算法进行改进,通过样本数据训练,测试数据检验,该网络能够较为准确地预测混煤一维燃烧硫释放的情况.
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| 关 键 词： | 混煤燃烧 神经网络 硫释放特性 预测 |
STUDY ON BP NEURAL NETWORK IN THE PREDICTION MODEL OF BLENDED COAL SULFUR RELEASING |
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| Wei Qingguo Liu Hantao , Su Tiexiong.STUDY ON BP NEURAL NETWORK IN THE PREDICTION MODEL OF BLENDED COAL SULFUR RELEASING[J].Coal Conversion,2010,33(2). |
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| Authors: | Wei Qingguo Liu Hantao Su Tiexiong |
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| Affiliation: | School of Mechatronice Engineering of North University of China/a>;030001 Taiyuan |
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| Abstract: | Research on the H2S and SO2 releasing characteristics by BP neural network is carried out,the data is validated by one-dimensional pulverized coal combustion system.A typical three-layer neural networks with 8 input neurons,6 connotative layer neurons,and 2 output neurons,the BP neural network arithmetic is improved by adding momentum item.Through trained by training samples and validated by test data,the model indicates that the BP neural network can predict the sulfur releasing characteristics well. |
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| Keywords: | blended coal combustion neural network sulfur releasing characteristics prediction |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
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