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何保, 李振南, 赵世杰. 基于多元非线性回归分析的露天煤矿涌水量预测[J]. 煤炭科学技术, 2018, (5).
引用本文: 何保, 李振南, 赵世杰. 基于多元非线性回归分析的露天煤矿涌水量预测[J]. 煤炭科学技术, 2018, (5).
HE Bao, LI Zhennan, ZHAO Shijie. Prediction on water inflow of surface mine based on multi-elementnonlinear regression analysis[J]. COAL SCIENCE AND TECHNOLOGY, 2018, (5).
Citation: HE Bao, LI Zhennan, ZHAO Shijie. Prediction on water inflow of surface mine based on multi-elementnonlinear regression analysis[J]. COAL SCIENCE AND TECHNOLOGY, 2018, (5).

基于多元非线性回归分析的露天煤矿涌水量预测

Prediction on water inflow of surface mine based on multi-elementnonlinear regression analysis

  • 摘要: 为准确预测元宝山露天煤矿涌水量,提高煤矿生产安全系数,基于矿区多降雨量和煤炭产量实测数据,以降雨量和煤炭产量为涌水量影响因子,运用水文地质比拟法和多元非线性回归分析法,分别建立矿区涌水量预测模型,通过对比分析,确定更精确的预测方法。研究结果表明:水文地质比拟法的比拟值与涌水量实测值相差较大,二者相关系数为-0.719,呈负相关,预测精度低;而多元非线性回归分析法的涌水量预测值与实测值相关系数达0.946,显著性水平检验R~2为0.894,能解释涌水量89.4%的变异,预测更精确,可作为今后矿区涌水量预测的依据,指导矿山安全生产。

     

    Abstract: In order to accurately predict the mine water inflow from Yuanbaoshan Surface Mine and to improve the safety coefficient of the coal mine production, based on the site measured data of several years’ rainfalls and coal productions in the mining area and the rainfall and coal production as the impact factors of the mine water inflow, a hydrogeologic analogy method and multi-element nonlinear regression analysis method was applied to individually establish the water inflow prediction model of the mining area. With the comparison analysis, a more accurate prediction method could be determined. The study results showed that the analogy value of the hydrogeologic analogy method would have a high difference to the site measured value of the water inflow, the correlation coefficient between the two values was -0.719 and was a negative correlation and the prediction accuracy was low. But the correlation coefficient between the predicted value of the water inflow obtained by the multi-element nonlinear regression analysis method and the site measured value was 0.946, the significance level test R2 was 0.894 and could explain the variation of the 89.4% water inflow. Thus the prediction would be more accurate and could be the basis to the prediction of the water inflow in the late mining area and to guide the mine safety production.

     

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