许满贵, 高帅帅, 曹艳军, 卢亚楠, 王娇娇. 基于灰色理论-多元回归分析的瓦斯含量预测[J]. 煤矿安全, 2018, 49(9): 211-214.
    引用本文: 许满贵, 高帅帅, 曹艳军, 卢亚楠, 王娇娇. 基于灰色理论-多元回归分析的瓦斯含量预测[J]. 煤矿安全, 2018, 49(9): 211-214.
    XU Mangui, GAO Shuaishuai, CAO Yanjun, LU Yanan, WANG Jiaojiao. Forecast of Gas Content Based on Gray Theory and Multiple Regression Analysis[J]. Safety in Coal Mines, 2018, 49(9): 211-214.
    Citation: XU Mangui, GAO Shuaishuai, CAO Yanjun, LU Yanan, WANG Jiaojiao. Forecast of Gas Content Based on Gray Theory and Multiple Regression Analysis[J]. Safety in Coal Mines, 2018, 49(9): 211-214.

    基于灰色理论-多元回归分析的瓦斯含量预测

    Forecast of Gas Content Based on Gray Theory and Multiple Regression Analysis

    • 摘要: 根据山阳矿5号煤层的地质情况,分析了瓦斯赋存影响因素,结合灰色关联度分析,得到各影响因素与瓦斯含量的关联度,从而得出影响因素的主次。在此基础上,采用多元回归分析法构建出预测矿井瓦斯含量的数学模型。为检验预测模型的可靠性,任选5个钻孔作为测试钻孔进行瓦斯含量预测,并与地勘时期测得的实际值比较分析,计算误差范围。结果表明:采用预测模型预测瓦斯含量,精度较高,效果较好,能满足工程要求。

       

      Abstract: According to the geological condition of No.5 coal seam in Shanyang Coal Mine, the influencing factors of gas occurrence are analyzed. Combined with the gray relational degree analysis method, the correlation degree of each influencing factor and the gas content is obtained, and the main and secondary fluencing factors are obtained. On this basis, the mathematical model for predicting gas content of mine is constructed by multiple regression analysis method. In order to test the reliability of the prediction model, five boreholes are selected as the test samples to measure the gas content. And compared with the actual value measured during the geological prospecting period, the error range is calculated. The results show that the prediction model can predict the gas content with higher precision and better effect, which can meet the engineering requirements.

       

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