| 粒子群优化算法在煤炭发热量预测中的应用 |
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| 引用本文： | 王建军,王世营,雷萌.粒子群优化算法在煤炭发热量预测中的应用[J].工矿自动化,2012,38(5):50-53. |
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| 作者姓名： | 王建军 王世营 雷萌 |
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| 作者单位： | 1. 大屯煤电(集团)有限责任公司,江苏徐州,221611
2. 中国矿业大学信电学院,江苏徐州,221008 |
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| 摘 要： | 根据已测定的煤中收到基全水、收到基灰分、干燥基灰分和收到基挥发分的含量,建立了基于BP神经网络的煤炭发热量预测模型,并采用粒子群优化算法优化BP神经网络的权值和阈值,实现了对煤炭发热量的快速预测。仿真及实验结果表明,经粒子群优化算法优化后的预测模型可用于煤质分析,且学习精度高,稳定性和鲁棒性好。
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| 关 键 词： | 煤质分析 发热量预测 粒子群优化算法 BP神经网络 |
Application of Particle Swarm Optimization Algorithm in Prediction of Coal Calorific Value |
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| WANG Jian-jun
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WANG Shi-ying
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LEI Meng.Application of Particle Swarm Optimization Algorithm in Prediction of Coal Calorific Value[J].Industry and Automation,2012,38(5):50-53. |
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| Authors: | WANG Jian-jun WANG Shi-ying LEI Meng |
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| Affiliation: | 1.Datun Coal and Electricity(Group) Co.,Ltd.,Xuzhou 221611,China. 2.School of Information and Electrical Engineering of CUMT.,Xuzhou 221008,China) |
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| Abstract: | A prediction model of coal calorific value based on BP neural network was established according to measured contents of total moisture of as received basis,ash of as received bass,ash of dry basis and volatile matter of as received basis in coal.Particle swarm optimization algorithm was used to optimize weights and thresholds of the BP neural network,which achieved rapid prediction of coal calorific value.The simulation and experimental results showed that the prediction model optimized by particle swarm optimization algorithm can be used for coal quality analysis,which has high study precision and good stability and robustness. |
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| Keywords: | coal quality analysis prediction of calorific value particle swarm optimization algorithm BP neural network |
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