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现代矿业 ›› 2013, Vol. 29 ›› Issue (12): 9-10+30.

• 采选工程 • 上一篇    下一篇

灰色关联理论在神经网络预测邻近层瓦斯涌出模型中的应用

吉振光   

  1. 晋煤集团寺河矿
  • 出版日期:2013-12-15 发布日期:2014-04-11

Application of Grey Correlation Theory in the Neural NetworkZof the Adjacent Layers of Gas Emission Forecast Model

Ji Zhenguang   

  1. Sihe Mine,Jincheng Anthracite Mine Group
  • Online:2013-12-15 Published:2014-04-11

摘要: 邻近层瓦斯通过裂隙通道向综采工作面运移是造成工作面瓦斯超限的重要原因之一。运用遗传算法改进的BP神经网络,建立邻近层瓦斯涌出预测模型,采用灰色关联理论,根据结构重要度选取影响因素,可以使综采工作面瓦斯预测结果更加准确,更有助于该工作面瓦斯治理。  

关键词: 灰色关联理论, 神经网络, 邻近层, 瓦斯涌出

Abstract: The gas of adjacent layers is migrated to the fully mechanized working face by slit channel.So,it is one of the important elements of transfinite gas in mine.The BP neural network is improved by the genetic algorithm,so as to obtain the prediction model of adjacent layers of gas emisson.According to the degree importance of structure,the grey correlation is adopted to make the prediction results of fully mechanized working face more exact.So,the research results can contribute to the gas controlling in the fully mechanized working face.   

Key words: Grey correlation theory, Neural network, Adjacent layers, Gas emission