Bayesian discriminant analysis for prediction of coal and gas outbursts and application

来源 :Mining Science and Technology | 被引量 : 0次 | 上传用户:puhongzhi
下载到本地 , 更方便阅读
声明 : 本文档内容版权归属内容提供方 , 如果您对本文有版权争议 , 可与客服联系进行内容授权或下架
论文部分内容阅读
Based on the principle of Bayesian discriminant analysis, we established a model of Bayesian discriminant analysis for predicting coal and gas outbursts. We selected five major indices which affect outbursts, i.e., initial speed of methane diffusion, a consistent coal coefficient, gas pressure, destructive style of coal and mining depth, as discriminating factors of the model. In our model, we divided the type of coal and gas outbursts into four grades regarded as four normal populations. We then obtained the corresponding discriminant functions through training a set of data from engineering examples as learning samples and evaluated their criteria by a back substitution method to verify the optimal properties of the model. Finally, we applied the model to the prediction of coal and gas outbursts in the Yunnan Enhong Mine. Our results coincided completely with the actual situation. These results show that a model of Bayesian discriminant analysis has excellent recognition performance, high prediction accuracy and a low error rate and is an effective method to predict coal and gas outbursts. Based on the principle of Bayesian discriminant analysis, we established a model of Bayesian discriminant analysis, we established a model of predicting coal and gas outbursts. We selected five major indices which affect outbursts, ie, initial speed of methane diffusion, a consistent coal coefficient, gas pressure, destructive style of coal and mining depth, as discriminating factors of the model. In our model, we divided the type of coal and gas outbursts into four grades as four normal populations. We then obtained the corresponding discriminant functions through training a set of data from engineering examples as learning samples and evaluated their criteria by a back substitution method to verify the optimal properties of the model. Finally, we applied the model to the prediction of coal and gas outbursts in the Yunnan Enhong Mine. Our results coinciding completely with the actual situation. These results show that a model of Bayesian discriminant analysis has excellent recognition performance, high prediction accuracy and a low error rate and is an effective method to predict coal and gas outbursts.
其他文献
青春一直是全世界电影导演所乐于关注、探讨、表现的母题。世界各国、不同的时代里,都曾经出现过优秀的青春电影。这些电影作为全世界不同国家、种族、信仰,不同年龄阶段的人们
在初中英语教学活动之中采取有效地游戏化教学方法,激发学生的学习兴趣,引导学生主动地加入到学习之中,创设趣味化的教学氛围,让学生爱上英语.
期刊
期刊
本文通过对荣华二采区10
刘远长大师简介  刘远长,1939年7月出生于江西吉安。中国工艺美术大师(国家级),系中国美术家协会会员、景德镇雕塑研究会秘书长,国际高岭陶艺学会名誉会长,享受国务院颁发的“政府特殊津贴”专家,第九届全国人大代表,“全国五一劳动奖章”获得者。
期刊
期刊
数形结合是教学学习中必须具备的能力,拥有数形结合思想,可以让学生更好地学习数学,更好地去理解数学的理论.将数学语言和图形结合,可以让学生更好地去理解和掌握数学理论,从
请下载后查看,本文暂不支持在线获取查看简介。 Please download to view, this article does not support online access to view profile.
期刊
期刊