城市地下矿山地表感知风险模糊ISM-BN评价模型与应用

在调研分析基础上, 采用模糊数学、解释结构模型和贝叶斯网络等方法, 构建了包含环境风险、事故风险、社会风险等方面共19个指标的城市地下矿山地表感知风险评价模型, 建立了城市地下矿山地表感知风险评价指标体系, 并将该体系应用于某城市地下铜矿山地表感知风险评价。结果表明, 该铜矿山地表感知的安全风险等级为Ⅳ级(即风险较低状态), 其中影响地表感知风险的关键性因素为地下水化学性指标和安全距离。

Fuzzy ISM-BN Evaluation Model for Perceptible Risks on Surface of Urban Underground Mines and Its Application

Based on the survey and analysis, fuzzy mathematics in combination with interpretive structure model (ISM) and Bayesian network (BN) was adopted to construct a risk evaluation model covering environmental risk, safety accident risk and social risk, with 19 influencing factors taken into consideration. An evaluation index system was then established for perceptible risks on the ground caused by underground mining, and was applied in the assessment of the perceptible risks on the surface of an urban underground copper mine. The results show that the perceptible risks on the surface of this copper mine is rated as grade Ⅳ, that is a lower level, and they are principally depended on the key factors of chemicals index of underground water and safe distance.