粗糙集理论在采空区分级指标权重确定中的应用  

Application of Rough Set Theory (RST) in Weight Determination for the Classification Index of Underground Goaf

作　　者：杨金林[1,2] 李夕兵[1,2] 周子龙[1,2] 陈红江[1,2] 

机构地区：[1]中南大学资源与安全工程学院,湖南长沙410083 [2]深部金属矿产开发与灾害控制湖南省重点实验室,湖南长沙410083

出　　处：《矿冶工程》2011年第2期8-11,共4页Mining and Metallurgical Engineering

基　　金：国家重点基础研究发展计划(973)(2010CB732004);湖南省研究生科研创新项目(CX2009B050)

摘　　要：为了准确计算采空区各个分级指标的权重,应用粗糙集理论对原始数据挖掘,将权重确定问题转化为粗糙集中属性重要性问题,通过计算分级指标与评判结果的粗糙依赖度来确定分级指标的权重。该方法克服了传统权重确定方法的主观性,从而提高了采空区分级的精度。通过广东大宝山采空区实例说明该方法合理、有效,为优化与改进采空区分级指标体系提供了合理的依据。In order to compute the weight factors of classification index for underground goaf accurately,rough sets theory is used to analyze the raw data,the significance of attributes among rough sets is estimated instead of weight determination.Weight factor is determined by calculating rough dependability between indexes and appraisement results.The approach overcomes the subjectivity in traditional weight determination method and improves the precision of underground goaf classification.It is reasonable for optimizing algorithm of underground goaf classification index system.Taking underground goaf in Dabaoshan Mine as an example,this new method proves to be effective and rational.

关 键 词：采空区 粗糙集理论 分级指标 权重 

分 类 号：TD32[矿业工程—矿井建设]