Research on Influencing Factors of LZ Coal Mine Safety Production

本文针对煤矿安全生产影响因素的复杂性与不确定性，综合运用层次分析法(AHP)与蒙特卡洛模拟(MCS)，构建了多层级风险评估模型。通过AHP将影响因素划分为人、设备、环境、管理四大准则层(涵盖26项具体指标)，量化各因素权重并揭示人因主导性(权重35%~45%)的显著特征；进一步利用MCS模拟判断矩阵的随机扰动，生成权重分布区间与置信度分析，解决了传统AHP依赖专家经验的主观偏差问题。研究表明，AHP-MCS耦合方法能够动态评估风险演化路径(如瓦斯浓度波动、设备老化风险)，并通过敏感性分析识别关键管控节点，为煤矿安全治理提供科学依据。This study addresses the complexity and uncertainty of coal mine safety production factors by integrating the Analytic Hierarchy Process (AHP) and Monte Carlo Simulation (MCS) to construct a multi-level risk assessment model. Through AHP, influencing factors are categorized into four major criteria layers—human, equipment, environment, and management, comprising 26 specific indicators. Quantitative analysis reveals the dominance of human factors (weights 35%~45%). MCS is further employed to simulate random perturbations in judgment matrices, generating weight distribution intervals and confidence level analysis, thereby addressing the subjective bias inherent in traditional AHP that relies on expert judgment. The research demonstrates that the AHP-MCS coupling method enables dynamic assessment of risk evolution paths (e.g., gas concentration fluctuations, equipment aging risks) and identifies critical control nodes through sensitivity analysis, providing a scientific basis for coal mine safety governance.