| 基于广义回归神经网络的瓦斯涌出量预测 |
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| 引用本文： | 葛江.基于广义回归神经网络的瓦斯涌出量预测[J].石家庄铁道大学学报(自然科学版),2013(4):105-108. |
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| 作者姓名： | 葛江 |
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| 作者单位： | 西南交通大学交通运输与物流学院,四川成都610031 |
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| 摘 要： | 简要介绍了瓦斯涌出量预测问题和广义回归神经网络（GRNN）的特点，指出与常用的BP神经网络相比，使用广义回归神经网络（GRNN）具有收敛迅速、人为干扰小等优点，适宜用于瓦斯涌出量的预测。并对一个案例进行预测，证明了广义回归神经网络（GRNN）可以满足实际生产的精度要求，较好解决瓦斯涌出量预测的问题。
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| 关 键 词： | 神经网络 涌出量 预测 GRNN |
Gas Emission Forecast Based on GRNN |
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| Ge Jiang.Gas Emission Forecast Based on GRNN[J].Journal of Shijiazhuang Railway Institute(Natural Science),2013(4):105-108. |
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| Authors: | Ge Jiang |
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| Institution: | Ge Jiang (School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China ) |
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| Abstract: | This paper introduces the characteristics of the gas emission forecast and the GRNN, and points out the rationality of using GRNN to forecast the gas emission and its advantage over the BP. The forecast is car- ried out based on a case, proving that GRNN can solve the problem of gas emission. |
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| Keywords: | neural gas emission forecast GRNN |
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