灰色线性回归组合模型在瓦斯涌出量预测中的应用

矿井瓦斯涌出量预测是新建矿井、新水平和新采区设计的主要依据。针对目前灰色理论预测模型和线性回归预测模型的缺点和不足,系统地推导了灰色线性回归组合预测模型。结合现场实测数据,并对比线性回归模型和灰色理论模型预测结果,发现该模型的预测精度分别提高了2.46%和1.35%,数据拟合的相关系数也有一定程度的提高。实证结果表明,灰色线性回归组合模型可以更好地预测矿井瓦斯涌出量。

Application of Grey Linear Regression Combination Model in Gas Emission Prediction

The prediction of the mine gas emission rate is the main basis for the design of a new mine,a new level and a new mining district.In this paper,a gray linear regression combination prediction model was systematically derived in accordance with the drawbacks and deficiencies of the current gray theory prediction model and the linear regression prediction model.It was found from the site measured data and the comparison of the prediction results of the linear regression model and the gray theory model that their prediction accuracy improved 2.46% and 1.35% respectively,and the correlation coefficient of data fitting was also improved.The experimental results showed that the gray linear regression combination prediction model can be used for the better prediction of the mine gas emission rate.