With the increasing mining depth,the threat of mine water inrush disaster is increasing day by day.How to accurately predict the risk of mine water inrush is a topic worthy of in-depth research.Aiming at the problem that the traditional methods do not dig deeply the effective information hidden in the monitoring data,taking the 11023 working face of Pan'er Coal Mine as the engineering background,a mine water inrush prediction model and mine water level prediction model based on LSTM are proposed,which use microseismic monitoring data and hydrological observation data to predict the mine water inrush and water level.The results show that the prediction results have small deviation from the real measured value,and have high accuracy,which has good application value and can provide technical guidance for the mine water prevention and control work.
关键词
煤矿开采/矿井突水风险预测/长短时记忆网络
Key words
coal mining/prediction of mine water inrush risk/long short-term memory network
维普
万方数据