矿山安全性模糊综合评价的新算法

A new algorithm of fuzzy comprehensive evaluation for mine safety

为了解决矿山安全性模糊评价过程中隶属度转换算法存在着目标分类不明确和出现冗余数值的问题,采用基于熵的数据挖掘方法,通过定义指标区分权,清除隶属度转换过程中的冗余数值,寻找对目标分类起作用的有效值计算隶属度,进行正确的隶属度转换并用于矿山安全性模糊综合评价中,应用实例说明了转换的全过程。研究结果表明:新的隶属度转换算法对矿山安全性评价具有更高的精确度。该方法有效地解决了模糊评价中的核心问题,对矿山的安全生产具有一定的指导意义。

In order to solve the problems of indefinite target classification in membership conversion algorithm and redundant values in mine safety fuzzy comprehensive evaluation,this study adopts data mining methods to eliminate the redundant values in the membership conversion by defining index distinction.Furthermore,by finding a valid value for the target classification,the membership is calculated to correct the membership conversion.A case study demonstrates the whole conversion process.Results show that the new membership conversion algorithm improves the accuracy of mine safety evaluation,and effectively solves the key issues of fuzzy assessment,and is of significance for the safety of mine production.