急倾斜煤层可放性的Bayes判别分析法  

Bayes Distinguishing Method to Distinguish Top Coal Caveability of Steep Inclined Seam

作　　者：王超[1] 李忠辉[1] 沈荣喜[1] 杜学胜[1] 

机构地区：[1]中国矿业大学安全工程学院,江苏徐州221008

出　　处：《煤炭科学技术》2010年第10期9-12,共4页Coal Science and Technology

基　　金：教育部新世纪优秀人才支持计划资助项目(NCET-06-0477);"十一五"国家科技支撑计划资助项目(2006BAK03B02-04)

摘　　要：为了对急倾斜煤层巷道放顶煤可放性进行研究,基于Bayes判别分析理论建立了急倾斜煤层顶煤可放性识别的Bayes判别分析模型。模型选用影响顶煤可放性的9个指标作为判别因子,将顶煤可放性分为4个等级作为Bayes判别分析的4个正态总体,以工程实例数据作为学习样本进行训练,建立相应的判别函数,并利用回代法对判别准则进行评价以验证模型的优良性。利用训练好的模型对典型的放顶煤可放性实例进行预测,结果与实际情况完全符合。研究结果表明,Bayes判别分析模型识别性能良好,预测精度高,误判率低,是顶煤可放性识别的一种有效方法,可以在实际工程中推广应用。In order to have the study on the top coal caveability of the gateway in the steep inclined seam,Based on the Bayes distinguished analysis theory,a Bayes distinguished analysis model to distinguish the top coal caveability in the steep inclined seam was established.The model selected 9 indexes affected to the top coal caveability as the distinguished factors.The top coal caveability could be divided into four grades as four obverse state ensembles of the Bayes distinguished analysis.Taking the engineering case data as the leaning sample for training,the related distinguished functions were established and the back substitution method was applied to evaluate the distinguished code in order to verify the excellent of the model.The well trained model was applied to pre-detect the typical top coal caveability case and the results and the actual conditions were fully fitted.The study results showed that the Bayes distinguished analysis model could have a good distinguishing performance,high predictionaccuracy,low miss distinguishing rate,could be a effective method to distinguish the top coal caveability and could be widely promoted and applied.

关 键 词：Bayes判别分析 急倾斜煤层 顶煤可放性 识别 

分 类 号：TD823.213[矿业工程—煤矿开采]