摘要
通过对埠村煤矿大量突水事例分析,认为工作面底板突水与工作面内是否存在断层、工作面下伏含水层的地下水的压力及富水性、含水层距工作面的距离、工作面宽度等因素相关。但各相关因素具有非显著性的特点,很难用一个准确的数学公式或统计公式来描述相互间的关系。利用大量的案例数据进行人工神经网络训练,建立一个人工神经网络系统,能够准确预测条带开采工作面的突水可能性。
Through the analysis on many water inrush events in Buchu Mine, the authors held that the water inrush from floor of a working face is related with many factors including the existence of faults in the face, the pressure of underground water and the enrichment in underlying water-bearing strata of the face, the distance of water-bearing strata to the face, the face width and so on. However, each factor has its marked feature, it is difficult to use an accurate mathematical formula or statistical formula to describe the correlations between them. Through artificial NN training with a number of cases and data, an artificial NN system was set up. which can be used to accurately predict the possibility of water inrush from a working face with partial extraction.
出处
《矿业安全与环保》
北大核心
2009年第4期23-25,共3页
Mining Safety & Environmental Protection
基金
江苏省博士后科研资助计划项目(0602028B)