基于大数据的矿山地质灾害预警模型

Mine geological disaster early warning model based on big data

针对传统地质灾害预警模型的预测精度不高的现象。通过大数据网络,研究矿山的地形、地貌、地层特性、地质构造等几个诱灾因子发生地质灾害的频率及损害程度,进而确定诱灾因子的概率取值,利用大数据计算方法,准确构建地质灾害预警模型。实验结果表明,矿山地质灾害预警模型进行地质灾害预测时具备良好的预测精度,具备有效性。

the prediction accuracy of traditional geological hazard early warning model is not high.Through large data network,the frequency and damage degree of geological hazards caused by several predisposing factors,such as topography,landform,stratum characteristics and geological structure,are studied,and then the probability value of predisposing factors is determined.The early warning model of geological hazards is accurately constructed by using large data calculation method.The experimental results show that the mine geological hazard early warning model has good prediction accuracy and effectiveness.