摘要
水文地质参数影响矿井涌水,而在岩溶山区矿山中,含水介质的非均质性、各向异性特别突出,水文地质参数的获取难度很大.因此,文章以弱化水文地质参数的依赖性为目标,应用相关分析和灰色系统理论模型对老鹰山煤矿1995—2013年的矿井涌水量进行拟合,建立了回归方程模型和GM(1,1)模型,并利用2014—2016年数据对模型预测结果进行了验证.结果表明相关分析中老鹰山煤矿矿井涌水量与降雨量密切相关,相关系数为0.835,模型曲线显示是变化形态上的预测,预测模型的精度达87.19%;灰色系统GM(1,1)预测模型的精度良好为82.34%,适合于具有灰色特征的地质数据的模拟、控制和预测,模型曲线显示的是变化趋势上的预测;相关分析法比灰色理论法预测精度高.研究成果为岩溶山区矿井涌水防治提供可靠技术支撑.
The hydrogeological parameters affect the mine water inflow,but in the karst mountain mines,the heterogeneity and anisotropy of the aqueous medium are particularly prominent,and the acquisition of hydrogeological parameters is very difficult,aiming at weakening the dependence of hydrogeological parameters.The correlation analysis and grey system theory model were used to fit the mine water inflow from1995 to 2013 in the Eagle Mountain coal mine.The regression equation model and the GM(1,1)model were established,and the data from 2014 to 2016 were used to verify the prediction results of the model.The results show that correlation analysis of Laoyingshan coal mine water inrush and rainfall is closely related,the correlation coefficient is 0.835,the model curve shows the change in the morphology of the forecast,the accuracy of the prediction model of 87.19%;gray system GM(1,1)prediction model The accuracy is 82.34%,which is suitable for the simulation,control and prediction of geological data with grey features.The model curve shows the prediction of change trends;the correlation analysis method has higher prediction accuracy than the grey theory method.The research results provide reliable technical support for the prevention of mine gushing in the karst mountainous area.
作者
褚双燕
王中美
王亚维
CHU Shuangyan;WANG Zhongmei;WANG Yawei(College of Resources and Environmental Engineering,Guizhou University,Guiyang Guizhou 550025,China)
出处
《新疆大学学报(自然科学版)》
CAS
2019年第1期106-113,共8页
Journal of Xinjiang University(Natural Science Edition)
基金
国家自然科学基金(41702270)
贵州省科技计划项目联合基金(黔科合LH字[2017]7284)
贵州省科技计划项目(黔科合支撑[2017]2858)
贵州省自然科学基金项目(黔科合J字[2014]2069)
贵州省水利厅科技专项经费项目(KT201506)
贵州大学2017年度学术新苗培养及创新探索专项(黔科合平台人才[2017]5788)