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为合理判定硫化矿石的自燃倾向性大小,将属性区间识别理论与信息熵理论结合,建立硫化矿石自燃倾向性综合评价的熵权属性区间识别模型。选取矿样的吸氧速度常数、自热点、着火点3项指标作为属性区间识别模型的基本判别因子,依据信息熵理论获得各判别指标的权重。给出矿样自燃倾向性的属性空间矩阵,采用均化系数将矿样的属性测度区间转化为综合属性测度;利用置信度识别准则和分级标准判别各个矿样的自燃倾向性。对采自国内典型硫化矿山的14个代表性矿样的室内实测值进行综合判定;结果表明,基于熵权的属性区间识别模型能更好地评价硫化矿石的自燃倾向性大小,如实反映出矿样的自燃特性。
In order to reasonably determine the spontaneous combustion propensity of sulfide ores, the attribute interval identification theory and information entropy theory are combined to establish the interval entropy weight attribute recognition model of spontaneous combustion tendency comprehensive evaluation of sulfide ores. Oxygen absorption rate constants of mineral samples, self-hot spots and ignition points are selected as the basic discriminant of attribute interval identification model, and the weight of each discriminant index is obtained according to the information entropy theory. The attribute space matrix of propensity to spontaneous combustion is given. The average coefficient is used to convert the attribute measure interval of ore samples into the comprehensive attribute measure. The confidence criteria and classification criteria are used to judge the spontaneous combustion propensity of each sample. The results show that the attribute interval identification model based on entropy weight can better evaluate the spontaneous combustion tendency of sulfide ores and accurately reflect the ore Like the spontaneous combustion characteristics.