主成分—费歇尔判别模型在煤与瓦斯突出等级预测中的应用

针对现有煤与瓦斯突出预测方法存在计算过程较复杂、预测主观性强、预测精度较低等问题,构建了主成分-费歇尔判别模型,并将其应用于某煤矿的煤与瓦斯突出等级预测。从瓦斯因素、煤体结构及地质构造方面分析得出了影响该矿煤与瓦斯突出的因素包括瓦斯压力、瓦斯含量及瓦斯放散初速度等指标。以影响该矿煤与瓦斯突出的23组实测数据为基础,首先利用主成分分析模型对影响该矿的煤与瓦斯突出因素进行降维,提取与指标相关度较高的5个主成分,然后将5个主成分输入费歇尔判别模型,并根据判别函数对样本进行煤与瓦斯突出等级预测。应用结果表明:主成分-费歇尔判别模型具有较高的可信性,能对煤与瓦斯突出等级进行准确预测,训练样本的正确率为100%,待测样本的预测结果也与该矿煤与瓦斯突出的实际情况相符,误判率为0,为准确预测煤与瓦斯突出提供了一种新方法。

Application of principal component-Fisher discrimination model in grade prediction of coal and gas outburst

In view of problems of complicated calculation process,strong subjectivity and low accuracy in existing prediction methods of coal and gas outburst,aprincipal component-Fisher discriminant model was constructed and applied to the prediction of coal and gas outburst grade in a coal mine.Based on analysis of gas factors,coal structure and geological structure,the factors that affect coal and gas outburst of the coal mine included gas pressure,gas content and initial velocity of gas release and so on were obtained.On the basis of 23 groups measured data of coal and gas outburst of the coal mine,firstly,the principal component analysis model was used to do dimension reduction of influencing factors of the mine coal and gas outburst,5 principal components with high index correlation were extracted.Then the5 principal components were input into Fisher discriminant model,and the grade of coal and gas outburst of samples was predicted according to discriminant function.The application results show that the principal component-Fisher discriminant model has high credibility,and can accurately predict coal and gas outburst grade,the training sample accuracy is 100%,the predicted results of the tested sample are also consistent with the actual situation of coal and gas outburst of the coal mine,misjudgment rate of 0,which provides a new method of accurate prediction of coal and gas outburst.