煤层底板突水危险性的Bayes判别分析模型及应用

发布时间：2018-05-06 03:26

本文选题：煤层 + 底板　；参考：《煤矿安全》2017年02期

【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。
[Abstract]:Based on the basic idea of Bayes discriminant analysis, the Bayes discriminant analysis model of coal seam floor water inrush hazard is established. Five indexes, such as water-rich aquifer, water pressure of aquifer, thickness of water-barrier layer, water conductivity of fault and development degree of structure, are selected as discriminant factors of the model, and 14 groups of coal seam measured data in different areas are taken as training samples. Bayes discriminant analysis model was established. In order to verify the accuracy of the model, 14 groups of coal seam measured data were identified by the method of backgeneration discriminant, and verified by an engineering example. The results show that the Bayes discriminant analysis model has a lower rate of misjudgment and can quickly and effectively distinguish the grade of water inrush from coal seam floor. It has strong applicability in practical engineering.
【作者单位】：平武县国土资源局;西南科技大学环境与资源学院;
【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)
【分类号】：TD745

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