| 采用遗传算法优化的煤粉着火特性BP神经网络预测模型 |
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| 引用本文： | 杨建国,翁善勇,赵虹,岑可法. 采用遗传算法优化的煤粉着火特性BP神经网络预测模型[J]. 动力工程, 2006, 26(1): 81-83,115 |
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| 作者姓名： | 杨建国 翁善勇 赵虹 岑可法 |
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| 作者单位： | 浙江大学,能源洁净利用与环境工程教育部重点实验室,杭州,310027 |
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| 摘 要： | 利用热分析（TG-DTG）数据建立了煤粉着火稳定性指数CI，它是煤粉着火温度与燃烧强度的综合反映。采用遗传算法（GA）对BP神经网络结构进行了优化，获得了影响煤粉着火稳定性指数CI的主要煤质指标（Mnd、And、Qnet、Qad、焦渣特征CRC）和最优BP神经网络的隐层数、神经元数、激活函数，建立了煤粉着火稳定性指数的优化BP神经网络预测模型。对20个校验样本进行了预测，得到了较高的预测精度。
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| 关 键 词： | 动力机械工程 预测模型 遗传算法 BP神经网络 煤粉 着火稳定性 |
| 文章编号： | 1000-6761（2006）01-081-03 |
| 收稿时间： | 2005-09-19 |
| 修稿时间： | 2005-09-19 |
An Optimized BP Network Model Using Genetic Algorithm for Predicting the Ignition-Stability Index of Pulverized Coal |
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| YANG Jian-guo,WENG Shan-yong,ZHAO Hong,CEN Ke-fa. An Optimized BP Network Model Using Genetic Algorithm for Predicting the Ignition-Stability Index of Pulverized Coal[J]. Power Engineering, 2006, 26(1): 81-83,115 |
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| Authors: | YANG Jian-guo WENG Shan-yong ZHAO Hong CEN Ke-fa |
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| Abstract: | An ignition stability index for pulverized coal(CI) has been contrived with IG-DTG analysis data.It comprehensively reflects the pulverized coal's ignition temperature and its combustion intensity.After optimizing,the BP network's structure with the help of genetic algorithm,the main coal indices (M_(ad),A_(ad),Q_(net,ad),O_(ad),coke slag characteristics) and the optimized BP neural network's concealed layers,neural cell number,as well as its activation function are obtained and the optimized BP neural network prediction model for predicting ignition indices of pulverized coal formed.Checks with 20 samples showed relatively high prediction precision.Figs 4 nd refs 8. |
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| Keywords: | power and mechanical engineering prediction model genetic algorithm BP neural network pulverized coal ignition stability |
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