Prediction of rock burst classification using cloud model with entropy weight  

熵权—云模型对岩爆等级的预测（英文）

作　　者：周科平[1] 林允[1] 邓红卫[1] 李杰林[1] 刘传举 

机构地区：[1]中南大学资源与安全工程学院,长沙410083

出　　处：《Transactions of Nonferrous Metals Society of China》2016年第7期1995-2002,共8页中国有色金属学报（英文版）

基　　金：Projects(51474252,51274253)supported by the National Natural Science Foundation of China;Project(2015CX005)supported by the Innovation Driven Plan of Central South University,China;Project(2016zzts095)supported by the Fundamental Research Funds for the Central Universities,China

摘　　要：The method of cloud model with entropy weight was adopted for the prediction of rock burst classification. Some main factors of rock burst including the uniaxial compressive strength （σc）, the tensile strength （σt）, the tangential stress （σθ）, the rock brittleness coefficient （σc/σt）, the stress coefficient （σθ /σc） and the elastic energy index （Wet） are chosen to establish evaluation index system. The entropy？cloud model and criterion are obtained through 209 sets of rock burst samples from underground rock projects. The sensitivity of indicators is analyzed and 209 sets of rock burst samples are discriminated by this model. The discriminant results of the entropy-cloud model are compared with those of Bayes, KNN and RF methods. The results show that the sensitivity order of those factors from high to low is σ_θ /σ_c, σ_θ, W_（ct）, σ_c/σ_t, σ_t, σ_c, and the entropy-cloud model has higher accuracy than Bayes, K-Nearest Neighbor algorithm （KNN） and Random Forest （RF） methods.采用熵权法和云模型判定岩爆等级。选用岩石的单轴抗压强度σ_c、单轴抗拉强度σ_t、切向应力σ_θ、岩石的压拉比σ_c/σ_t、岩石的应力系数σ_θ/σ_c和岩石的弹性变形指数W_(et)作为岩爆等级判定的因素建立岩爆评价指标体系。以收集到209组工程中的实际岩爆情况及数据作为样本进行分析计算,建立岩爆等级判定的熵权-云模型。运用该分析模型分析岩爆评价指标体系中评价指标的敏感性,并对收集到的工程实例岩爆情况进行判定,将结果与Bayes、KNN和随机森林方法的判定结果进行比较。研究表明:评价指标体系中指标敏感性由大到小的顺序为:σ_θ /σ_c, σ_θ, W_(ct), σ_c/σ_t, σ_t, σ_c,;熵权-云模型的判别准确率比Bayes、K最邻近结点算法(KNN)和随机森林(RF)方法高。

关 键 词：rock burst PREDICTION cloud model entropy weight sensitivity 

分 类 号：TU45[建筑科学—岩土工程]