基于改进AHP-TOPSIS的煤矿顶板灾害风险分析

Risk Analysis of Coal Mine Roof Disaster Based on Improved AHP-TOPSIS

  • 摘要: 为科学合理地评估煤矿顶板灾害风险,有效预防和减少深部煤炭开采过程中的顶板事故,构建了基于熵权修正AHP-TOPSIS的风险评价模型。该模型从地质环境、技术、管理及行为四个维度出发,建立了包含20项二级指标的评价体系,通过熵权法对AHP权重进行修正,有效克服了单一赋权方法的主观局限性;基于指标临界值建立了四级风险判定准则。蒙特卡洛模拟结果表明,新模型对±10%的权重扰动具有较强的鲁棒性,其Ⅱ级风险判定的概率达到96.7%,相较于传统AHP方法(80.1%)提升了16.6个百分点。实例验证显示,模型的预测结果(Ⅱ级中等风险)与实际案例高度吻合。此外,敏感性分析识别出地质构造和空顶作业为关键敏感指标。该模型通过组合赋权与稳定性优化,为顶板灾害防治提供了可靠的定量化决策工具。

     

    Abstract: In order to scientifically and reasonably evaluate the risks of coal mine roof disasters, effectively prevent and reduce roof accidents during the deep coal mining process, a risk evaluation model based on entropy weight modified AHP-TOPSIS is constructed. This model establishes an evaluation system consisting of 20 items of second-level indicators from four dimensions like geological environment, technology, management, and behavior, the AHP weights are conducted to be modified through entropy weight method, the subjective limitations of single weighting method are effectively overcame; A four-level risk judgement criterion is established based on the critical value of indicator. The Monte Carlo simulation results show that the new model has relatively strong robustness to weight perturbations of ±10%, the probability of its level Ⅱ risk judgement reaches 96.7%, which is 16.6 percentage points higher than that of the traditional AHP method (80.1%). The actual case verification indicates that the model prediction result (Level Ⅱ moderate risk) are highly consistent with the actual case. Besides that, the sensitivity analysis identifies geological structures and empty roof operations as key sensitive indicators. This model provides a reliable quantitative decision-making tool for roof disaster prevention and control by combination weighting and stability optimization.

     

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