基于大数据分析的冲击地压预测及防治技术研究

Research on rock burst prediction and control technology based on big data analysis

文章旨在通过大数据分析技术,提高对冲击地压的预测准确性和预警能力,为煤矿安全生产提供技术支持和保障。通过收集并整合大量的煤矿地质、地下水、地应力等多维度数据,构建冲击地压的预测模型,并利用机器学习和深度学习算法进行模型训练和优化。研究结果表明,基于大数据分析的冲击地压预测模型能够准确预测地质灾害的发生概率和影响程度,提前发现地质灾害隐患,为矿山安全管理提供重要决策依据。

This paper aims to improve the prediction accuracy and early warning ability of rock burst through big data analysis technology,and provide technical support and guarantee for coal mine safety production.By collecting and integrating a large number of multi-dimensional data such as coal mine geology,groundwater and ground stress,the prediction model of rock burst is built,and machine learning and deep learning algorithms are used for model training and optimization.The results show that the rock burst prediction model based on big data analysis can accurately predict the occurrence probability and influence degree of geological disasters,find the hidden danger of geological disasters in advance,and provide an important decision-making basis for mine safety management.