摘要
文章以赵庄煤矿2号井3号煤层地质条件为背景,依据煤层瓦斯含量影响因素,应用人工神经网络的理论与方法,建立了煤层瓦斯含量的BP神经网络预测模型。应用该网络对井田范围内未知区域进行煤层瓦斯含量预测和分析,从而绘制出较为准确的井田瓦斯含量预测图。为煤层瓦斯含量预测提供新的研究方法和研究手段。
Based on the geological condition of No. 3 coal seam of Zhaozhuang No. 2 well and influence factor of gas content, build eval- uating model of BP Neural Network on gas content of coal seam by using artificial neural network theory and method. Based on the net- work, this paper predicts and analyzes the gas content of the unexplored area in the well field, which sets the stage for drawing the pre- diction map of gas content. It provides a new research method and means for predicting gas content of coal seam.
出处
《煤》
2012年第10期18-20,54,共4页
Coal
关键词
瓦斯预测
BP神经网络
层节点
传输函数
gas prediction
BP neural network
layer node
transfer - function
