覆盖粗糙Vague集的不确定性度量研究  

Research on Uncertainty Measurement for Covering Rough-Vague Sets

作　　者：徐久成 张倩倩[1] 

机构地区：[1]河南师范大学计算机与信息技术学院,新乡453007

出　　处：《计算机科学》2010年第10期225-227,282,共4页Computer Science

基　　金：国家自然科学基金项目(60873104);河南省高校新世纪优秀人才支持计划(2006HANCET-19);河南省教育厅自然科学基金项目(2008B520019)资助

摘　　要：在覆盖粗糙集理论研究的基础上,将粗糙集理论与Vague集理论相融合,研究基于覆盖的粗糙Vague集模型及其相关性质。为了更好地度量该模型的不确定性,首先定义了知识含量测度,用于度量覆盖对论域中对象分类能力产生的不确定性,此种度量方法体现了分类知识的本质特征;同时结合边界域大小的度量方法,定义了C-粗糙度的概念用于度量覆盖粗糙Vague集的不确定性。实例分析结果表明了这种度量方法的简洁高效性。On the researching of covering rough sets theory,Rough-Vague sets model and its properties based on cover were researched by integrating rough sets theory and vague sets theory.In order to measured this model＇s uncertainty perfectly,firstly,it measured the uncertainty of the classification capability of cover by defining knowledge capacity measure.Such method reflects the essential characteristic of knowledge classification.And then it defined C-roughness to measure the model＇s uncertainty effectively by combining knowledge capacity and roughness（the measure of border field）.The concisely and validity for this measurement were proved by analyzing example.

关 键 词：VAGUE集 粗糙VAGUE集 知识含量 不确定性 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]