Feasibility of stochastic gradient boosting approach for predicting rockburst damage in burst-prone mines

作     者：周健 史秀志 黄仁东 邱贤阳 陈冲 Jian ZHOU;Xiu-zhi SHI;Ren-dong HUANG;Xian-yang QIU;Chong CHEN

作者机构：中南大学资源与安全工程学院长沙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：2016年第26卷第7期

页      面：1938-1945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(2015CX005)supported by the Innovation Driven Plan of Central South University of China Project supported by the Sheng Hua Lie Ying Program of Central South University,China 

主　　题：burst-prone mine rockburst damage stochastic gradient boosting method 

摘      要：The database of 254 rockburst events was examined for rockburst damage classification using stochastic gradient boosting （SGB） methods. Five potentially relevant indicators including the stress condition factor, the ground support system capacity, the excavation span, the geological structure and the peak particle velocity of rockburst sites were analyzed. The performance of the model was evaluated using a 10 folds cross-validation （CV） procedure with 80%of original data during modeling, and an external testing set （20%） was employed to validate the prediction performance of the SGB model. Two accuracy measures for multi-class problems were employed： classification accuracy rate and Cohen’s Kappa. The accuracy analysis together with Kappa for the rockburst damage dataset reveals that the SGB model for the prediction of rockburst damage is acceptable.