中国有色金属学报(英文版)
Transactions of Nonferrous Metals Society of China
| Vol. 22 No. 2 February 2012 |
complicated goaf in mines and its application
（1. School of Resources and Safety Engineering, Central South University, Changsha 410083, China;
2. Hunan Key Laboratory of Resources Exploitation and Hazard Control for Deep Metal Mines,
Changsha 410083, China）
Abstract: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 goaf, were selected as discriminant indexes in the stability analysis of goaf. The actual data of 40 goafs 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.
Key words: goaf; risky identification; Bayes discriminant analysis; metal mines
