The occurrence of unpredictable hazards are frequent with the increased depth of mining, especially the hazards caused by stress concentration. In order to mitigate the negative effectiveness results from mining-induce stress, various approaches have been employed in underground mines. Destress blasting, as an efficient method, has gained a lot of popularity in recent years. However, it is crucial to estimate the destressability of specific area before conducting destress blasting. In this study a combination model on the basis of both unascertained measurement (UM) and entropy coefficients was applied to observe the performance of destressability evaluation. Eight representative parameters, i.e., stiffness of the rock mass, brittleness of the rock mass, degree of fracturing, proximity to failure, destress blast orientation, width of the target zone, unit explosive energy, and confinement of the charges were chosen as initial input parameters, and their membership distributions were described by four types of membership methodologies, i.e., line, parabolic curve, exponential curve, and sine curve. Meanwhile, the weights of each index could be computed based on the single measurement matrix. Then, destressability of the samples was easily identified with Euclidean distance and comprehensive measurement vectors which were computed by single measurement vectors and weight coefficients. Finally, it was found that the assessment results are in accordance with those calculated by destressability index. It can be concluded that the proposed hybrid model is able to eliminate the disturbance of subjective factors and ensure the reliability of these outcomes. At the same time, it can provide a novel idea/process for the destressability evaluation.

中文翻译：

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一种新的信息熵和不确定测量混合模型，具有不同隶属函数，用于评估易爆地下矿山的去应力性

随着开采深度的增加，不可预知的危害频繁发生，尤其是应力集中引起的危害。为了减轻采矿诱导应力的负面影响，地下矿山采用了各种方法。减压爆破作为一种有效的方法，近年来受到了广泛的欢迎。然而，在进行去应力爆破之前估计特定区域的去应力能力是至关重要的。在这项研究中，基于不确定性测量 (UM) 和熵系数的组合模型被应用于观察去应力评估的性能。八个代表性参数，即岩体的刚度、岩体的脆性、破裂程度、接近破坏的程度、去应力爆破方向、选取靶区宽度、单位爆炸能量和装药约束作为初始输入参数，采用直线、抛物线、指数曲线和正弦曲线四种隶属方法描述其隶属度分布。同时，可以基于单个测量矩阵计算每个指标的权重。然后，用欧氏距离和综合测量矢量很容易地识别样品的去应力性，综合测量矢量由单个测量向量和权重系数计算。最后发现评估结果与去应力指数计算的结果一致。可以得出结论，所提出的混合模型能够消除主观因素的干扰并确保这些结果的可靠性。同时，