摘要
介绍了Ziarko’s变精度粗糙集模型和粗糙模糊集模型,找出了它们的不足。基于支集相对错误分类率及误差参数β(0≤β<0.5),提出了变精度粗糙模糊集模型,讨论了模型中β上、下近似算子的性质;分析了该模型与Ziarko’s变精度粗糙集模型和粗糙模糊集模型的关系;最后给出了该模型中近似约简的定义和方法,并通过实例分析说明了约简算法的有效性。
Ziarko＇s variable precision rough set model and rough fuzzy set model are introduced and the drawbacks of them are found.Based on support relative error ratio and error parameterβ（0≤β〈0.5）,the variable precision rough fuzzy set model is proposed.The basic properties of approximation operators are investigated.The relation between this model and Ziarko＇s variable precision rough set model and rough fuzzy set model is analysed in detail.Finally,the definitions and the approaches of approxima- tion reduction are discussed ,an example is given to illustrate the validity of the presented algorithms.
出处
《计算机工程与应用》
CSCD
北大核心
2007年第23期15-17,31,共4页
Computer Engineering and Applications
基金
国家自然科学基金(the National Natural Science Foundation of China under Grant No.60474022)
高等院校博士学科点专项科研基金(the China Specialized Research Fund for the Doctoral Program of Higher Education under Grant No.20060613007)
河南科技大学人才科学研究基金(No.09001172)
关键词
变精度粗糙集
粗糙模糊集
变精度粗糙模糊集
近似约简
variable precision rough set
rough fuzzy set
variable precision rough fuzzy set
approximation reduction
