姜洋. 基于群决策层次分析和因子分析的CW-FCEM煤矿冲击地压评价模型[J]. 煤矿安全, 2019, 50(9): 187-191.
    引用本文: 姜洋. 基于群决策层次分析和因子分析的CW-FCEM煤矿冲击地压评价模型[J]. 煤矿安全, 2019, 50(9): 187-191.
    JIANG Yang. CW-FCEM Evaluation Model of Rock Burst in Coal Mine Based on Group Decision Analytic Hierarchy Process and Factor Analysis[J]. Safety in Coal Mines, 2019, 50(9): 187-191.
    Citation: JIANG Yang. CW-FCEM Evaluation Model of Rock Burst in Coal Mine Based on Group Decision Analytic Hierarchy Process and Factor Analysis[J]. Safety in Coal Mines, 2019, 50(9): 187-191.

    基于群决策层次分析和因子分析的CW-FCEM煤矿冲击地压评价模型

    CW-FCEM Evaluation Model of Rock Burst in Coal Mine Based on Group Decision Analytic Hierarchy Process and Factor Analysis

    • 摘要: 煤矿冲击地压评价准确性较低,主要是因为难以确定合理的评价指标权重。针对此问题,提出了评价指标组合赋权法,首先利用群决策层次分析法确定指标的主观权重,然后利用因子分析法确定指标的客观权重,最后通过乘法归一化公式将主观权重和客观权重结合为组合权重,获得合理的指标权重,有效消除了主观赋权时的人为影响,同时也避免了客观赋权时过于绝对化的问题。将组合权重引入到模糊综合评价法中,对某煤矿冲击地压危险性进行评价,评价结果为“较安全”,符合工程实际。由此表明,基于群决策层次分析法和因子分析的CW-FCEM耦合评价模型评价准确,精度较高。

       

      Abstract: The evaluation accuracy of rock burst in coal mine is low, mainly because it is difficult to determine the reasonable evaluation index weight. To solve this problem, the evaluation index combination weighting method is proposed. Firstly, the subjective weight of the index is determined by the analytic hierarchy process of group decision-making, and then the objective weight of the index is determined by the factor analysis method. Finally, through the multiplication normalization formula, the subjective weight and objective weight are combined to get a reasonable index weight, which effectively eliminates the artificial influence when subjective weight is given, and avoids the problem of too absolute when objective weight is given. The combination weight is introduced into the fuzzy comprehensive evaluation method to evaluate the danger of rock burst in a coal mine, and the evaluation result is “safer”, which accords with the engineering practice. The results show that the CW-FCEM coupling evaluation model based on AHP and factor analysis is accurate and accurate.

       

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