正态分布模型在煤与瓦斯突出危险程度诊断中的应用

Application of normal distribution model in the diagnosis of coal and gas outburst risk

煤与瓦斯突出与其影响因素间存在着非线性关系,数据样本的采集具有随机性。为了提高突出危险等级预测的准确性和增强预测预报方法的实用性,选取开采深度、瓦斯压力等5项影响判别因子,建立了基于正态分布的煤与瓦斯突出判别模型,该模型的结构特点是判别因子之间呈线性关系,而判别因子与突出危险等级间呈非线性关系。模型参数的确定采用了极大似然函数估计法,并利用MATLAB所提供的求解约束最优化问题的内置函数完成计算。通过对20组样本的学习和对5组样本的预测,验证了该模型在煤与瓦斯突出危险等级判别中的有效性、准确性。另外,该模型结构简单,实用性强,易于程序实现,有借鉴价值。

There is a nonlinear relationship between coal and gas outburst and its influence factors,the randomness of data samples collected.In order to improve the accuracy of outburst dangerous grade prediction and enhance the forecasting method of the utility,selecting five impact of mining depth,gas pressure and other discriminating factors,established coal and gas outburst discriminant model based on the normal distribution,the structure characteristics of the model is a linear relationship between the discriminant factor,but the relationship is nonlinear between factors and discriminant the outburst dangerous grade.Determine model parameters using a maximum likelihood estimation method function,and use MATLAB for solving constrained optimization problems provided built-in functions to complete the calculations.Through the 20 groups of sample learning and prediction of 5 groups of samples,Through the 20 groups of sample learning and prediction of 5 groups of samples,verify the validity and accuracy of the model in the coal and gasoutburst dangerous grade discrimination.In addition,the model structure is simple,strong practicability,easy to program implementation,there is reference value.