煤层底板突水危险性的Bayes判别分析模型及应用  

Bayes Discriminant Analysis Model for Water Inrush Risk from Coal Seam Floor and its Application

作　　者：李红梅[1] 赵春侠[2] 刘年平[2] 王大国[2] 

机构地区：[1]平武县国土资源局,四川绵阳621000 [2]西南科技大学环境与资源学院,四川绵阳621010

出　　处：《煤矿安全》2017年第2期174-177,共4页Safety in Coal Mines

基　　金：四川省教育厅科研资助项目(16CZ0013;15ZB0124);绵阳市科技计划资助项目(14S-02-6)

摘　　要：基于Bayes判别分析的基本思想,建立煤层底板突水危险性的Bayes判别分析模型。选用煤层的含水层富水性、含水层水压、隔水层厚度、断层导水性和构造发育程度5个指标作为该模型的判别因子,以不同地区煤矿的14组煤层实测数据作为训练样本,建立了Bayes判别分析模型。为了验证模型的准确性,用回代判别方法对14组煤层实测数据进行判别,并用工程实例进行了验证。研究结果表明,Bayes判别分析模型误判率较低,能快速有效地判别出煤层底板突水危险性的等级,在实际工程中有较强的适用性。Based on the basic idea of Bayes discriminant analysis method, we established Bayes discriminant analysis model for evaluating water inrush risk from coal seam floor. Five indicators such as aquifer property, water head, water-resisting layer thickness, fault permeability and fractures development level were used as discriminant factors in the model. Fourteen groups of measured data on coal seam from diffenent coal mines were regarded as training samples, then the Bayes discriminant model was set up. Fourteen groups of experimental data of coal seam were discriminated by back substitution discriminant method and then the model was used in practical engineering. The results show that misjudgment rate of the Bayes discriminant analysis model is low and it can effectively distinguish the coal floor water inrush risk level. So the model can be better applied to practical engineering.

关 键 词：煤层 底板 突水 BAYES方法 判别分析 

分 类 号：TD745[矿业工程—矿井通风与安全]