Bayes discriminant analysis method to identify risky of complicated goaf in mines and its application

作     者：胡玉玺 李夕兵 HU Yu-xi;LI Xi-bing

作者机构：中南大学资源与安全工程学院长沙410083 深部金属矿产开发与灾害控制湖南省重点试验室长沙410083 

出 版 物：《Transactions of Nonferrous Metals Society of China》 (中国有色金属学报（英文版）)

年 卷 期：2012年第22卷第2期

页      面：425-431页

核心收录：

学科分类：081901[工学-采矿工程] 0819[工学-矿业工程] 08[工学] 

基　　金：Project (2010CB732004) supported by the National Basic Research Program of China 

主　　题：goaf risky identification Bayes discriminant analysis metal mines 

摘      要：A Bayes discriminant analysis method to identify the risky of complicated goaf in mines was presented. Nine factors influencing the stability of goaf risky, including uniaxial compressive strength of rock, elastic modulus of rock, rock quality designation （RQD）, area ratio of pillar, ratio of width to height of pillar, depth of ore body, volume of goaf, dip of ore body and area of goal, were selected as discriminant indexes in the stability analysis of goal. The actual data of 40 goals were used as training samples to establish a discriminant analysis model to identify the stability of goaf. The results show that this discriminant analysis model has high precision and misdiscriminant ratio is 0.025 in re-substitution process. The instability identification of a metal mine was distinguished by using this model and the identification result is identical with that of practical situation.