冲击地压危险性等级识别的随机森林模型及应用  

Determination of classification of rock burst risk based on random forest approach and its application

作　　者：李宝富[1,2] 刘永磊 

机构地区：[1]河南理工大学能源科学与工程学院,焦作454000 [2]哈密职业技术学院,哈密839000

出　　处：《科技导报》2015年第1期57-62,共6页Science & Technology Review

基　　金：国家自然科学基金项目(41204035)

摘　　要：为快速、准确地预测冲击地压危险性,借鉴随机森林理论,选取影响冲击地压的10项主要因素:煤层、倾角、埋深、构造情况、倾角变化、煤厚变化、瓦斯浓度、顶板管理、卸压、响煤炮声作为判别因子,建立冲击地压危险性识别的随机森林模型。利用重庆砚石台矿24组实测数据作为学习样本建立随机森林分类器,在对样本分类的同时,计算预测变量的重要性值GI,发现构造情况为最重要的评价指标,其后是响煤炮声和倾角。利用其他12组现场数据作为预测样本对该模型进行测试,预测结果与实际情况吻合较好。Arandom forest（RF） modelfor rock burst identification was established on the basis of the RF theory to forecast rock burst risk rapidly and accurately. Ten indices,ie,coal seam,dip angle,buried depth,structure situation,change of dip angle,change of coal thickness,gas concentration,roof management,pressure relief and shooting were used as the criterion indices for rock burst prediction in the proposed model on the basis of analysis of rock burst impact. Twenty-four typical rock burst instances of a coal mine were used to createa RF classifier. RF is a combination of tree predictors,and variable importance is measured by Gini importance（GI） when the forest grows. The GI shows that structure situation was the most important indicator,followed by shooting and dip angle. Another 12 groups of rock burst instances were tested as forecast samples,and the predicted results were in accordance with actual situation.

关 键 词：冲击地压 随机森林 变量重要度 

分 类 号：TD324[矿业工程—矿井建设]