摘要
根据陕西某煤矿的水文地质条件,分析了影响该矿井涌水量的主要因素及指标,运用BP神经网络和大井法分别预测其二、三采区的不同工作面涌水量,并对计算结果进行比较分析。分析结果表明,BP神经网络模型的预测结果较为准确,可将其作为该矿井制定疏水降压方案的依据。
Main factors and indicators that affect water inflow of a coal mine of Shaanxi were analyzed according to its hydrogeological conditions.BP neural network and large-well method were used to predict water inflow of different working faces of the second and third districts,and results of the two methods were compared.The analysis results show that the predict result of BP neural network model is more accurate,it can be used as basis for development of mine drainage and pressure decreasing program.
出处
《工矿自动化》
北大核心
2016年第7期66-69,共4页
Journal Of Mine Automation
基金
防灾减灾青年科技基金项目(201201)
河北省教育厅高等学校科学研究计划项目(Z2013027)
关键词
涌水量预测
BP神经网络
大井法
prediction of water inflow
BP neural network
large-well method
