基于神经网络的煤与瓦斯突出矿井等级划分方法  

The measure to grade the coal and gas outburst based on the nerve network

作　　者：李树刚[1] 刘志云[1] 林海飞[1] 

机构地区：[1]西安科技大学能源学院,陕西西安710054

出　　处：《煤田地质与勘探》2005年第1期19-21,共3页Coal Geology & Exploration

基　　金：陕西省教育厅专项科研计划项目 (0 2JK0 82 )

摘　　要：针对我国煤炭行业中对突出矿井同一定级 ,实施同一安全管理的现象 ,从分析工作系统的灾害模型出发 ,给出了突出矿井等级划分的评价指标体系 ,应用灰色系统和证据理论的方法给出了神经网络训练的样本。在此基础上 ,提出了危险信度的概念 ,用以衡量突出矿井危险程度 ,编制了神经网络 ,并对其进行训练。应用训练好的神经网络 ,对淮南矿区的几个突出矿井进行了工程验证。Aiming at the electrophoresis of classing outburst mines and practicing the same safety management in our country’s coal industry, with analyzing accident model in work systems, brought up evaluation indexes system. Applying the methods of gray system synthesize evaluation and proof theories, got the outburst dangerous grade samples. Based on it, the dangerous degree measure (dangerous believe degree) was put forward, applied the trained neural network to a few outburst mines engineering verification of Huainan diggings. The research of this text for the demarcation method of outburst mines dangerous grade of out country outburst mines has the certain guidance meaning for establish our country demarcation method and evaluation standard of outburst mines dangerous degree.

关 键 词：煤与瓦斯突出 等级划分 危险信度 神经网络 

分 类 号：TD713[矿业工程—矿井通风与安全]