基于大样本不完整数据的岩爆致因特征及预测模型
摘要
In order to distinguish the sensitivity factors affecting rockburst and construct a rockburst prediction method under the condition of incomplete data cases, a large sample database is established on the basis of collecting 429 groups of rockburst cases at home and abroad, and the distribution characteristics and regulation of rockburst disaster-inducing factors were summarized.Six evaluation indexes, including buried depth, uniaxial compressive strength of rock, uniaxial tensile strength of rock, maximum tangential stress of surrounding rock, rock elastic energy index and integrity coefficient of rock mass, are selected to establish a rockburst probability prediction model based on large and incomplete data set by using Bayesian network, and the sensitivity analysis and engineering application are carried out.Through analysis, it is found that