基于RS-云模型的硫化矿石自燃倾向性综合评价

为实现硫化矿石自燃倾向性的综合评价，应用云理论，选取矿样的氧化质量增加率、自热点和自燃点等定量化指标构建了评价指标体系，运用粗糙集法（Rough Set, RS）计算各评价指标权重，依据分级标准对云模型进行标准化，进而建立硫化矿石自燃倾向性分级的RS-标准云模型。以30组工程实例进行模型检验，并在实际工程中进行应用。结果表明:RS-标准云模型的判别结果与实际结果较吻合，且判别准确率高于贝叶斯(Bayesian, Bayes)方法，表明RS-标准云模型在硫化矿石自燃倾向性综合评价中具有良好的实用性和可靠性，可为矿山的硫化矿石自燃灾害的研究提供一种新思路。

Comprehensive evaluation on spontaneous combustion tendency of sulfide ore based on RS-cloud model

In order to achieve the comprehensive evaluation on the spontaneous combustion tendency of sulfide ore, an evaluation index system was established by selecting three quantitative indexes including the oxidation mass increment rate, self-heating temperature and spontaneous combustion temperature of ore sample based on the cloud theory, and the weight of each evaluation index was calculated by using the rough set (RS) method. The cloud model was standardized according to the grading standard, then a RS-standardized cloud model for the grading of spontaneous combustion tendency of sulfide ore was established. The model was validated with 30 groups of engineering case, and applied in the practical engineering. The results showed that the judgment results of the proposed model were in agreement with the practical results, and the judgment accuracy was higher than the Bayes method. It showed that the RS-standardized cloud model has good practicability and reliability in the comprehensive evaluation on spontaneous combustion tendency of sulfide ore, and provides a new idea for the research on the spontaneous combustion disaster of sulfide ore in mine.