本文選題：煤層 + 底板��； 參考：《煤礦安全》2017年02期

【摘要】：基于Bayes判別分析的基本思想,建立煤層底板突水危險性的Bayes判別分析模型。選用煤層的含水層富水性、含水層水壓、隔水層厚度、斷層導(dǎo)水性和構(gòu)造發(fā)育程度5個指標(biāo)作為該模型的判別因子,以不同地區(qū)煤礦的14組煤層實測數(shù)據(jù)作為訓(xùn)練樣本,建立了Bayes判別分析模型。為了驗證模型的準(zhǔn)確性,用回代判別方法對14組煤層實測數(shù)據(jù)進(jìn)行判別,并用工程實例進(jìn)行了驗證。研究結(jié)果表明,Bayes判別分析模型誤判率較低,能快速有效地判別出煤層底板突水危險性的等級,在實際工程中有較強(qiáng)的適用性。
[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.
【作者單位】： 平武縣國土資源局;西南科技大學(xué)環(huán)境與資源學(xué)院;
【基金】：四川省教育廳科研資助項目(16CZ0013,15ZB0124) 綿陽市科技計劃資助項目(14S-02-6)
【分類號】：TD745

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