基于神经网络算法的煤矿瓦斯涌出量预测模型研究  

Research on Coal Mine Gas Emission Forecasting Model Based on Neural Network Algorithm

作　　者：白云霄[1] 

机构地区：[1]陕西科技大学理学院,西安710021

出　　处：《煤炭技术》2012年第11期104-106,共3页Coal Technology

摘　　要：在煤矿生产过程中存在着瓦斯涌出现象,严重威胁着煤矿的安全生产。瓦斯涌出检查在矿井设计、建设和开采作业过程中显得尤为重要。文章采用神经网络有效地对矿井瓦斯气量进行检测分析,利用分析结果进行准确预测。文中将介绍神经网络预测的整体构建过程,结合仿真实例,分析煤矿瓦斯涌出量预测模型的可靠性。The gas emission exists in the mine prociucuon process, it＇ a serious threat to the, safe production of coal mines. The gas emission check is particularly important in the mine design, construction and mining operations. In the papre, the gas emission is checked and analyzed by using the neural network. The analyzing results are used to accurately predict gas emision. The overall buile process of the neural network foreeasf is introduced. Combined with simulation examples, the reliability of the coal mine gas emission model is analyzed.

关 键 词：煤矿 神经网络 瓦斯预测 

分 类 号：TD712[矿业工程—矿井通风与安全]