A roughness measure of fuzzy sets from the perspective of distance

被引:9
|
作者
Hu, J. [1 ,2 ]
Pedrycz, W. [2 ,3 ,4 ]
Wang, G. [1 ]
机构
[1] Chongqing Univ Posts & Telecommun, Chongqing Key Lab Computat Intelligence, Chongqing, Peoples R China
[2] Univ Alberta, Dept Elect & Comp Engn, Edmonton, AB, Canada
[3] King Abdulaziz Univ, Fac Engn, Dept Elect & Comp Engn, Jeddah 21413, Saudi Arabia
[4] Polish Acad Sci, Syst Res Inst, PL-01447 Warsaw, Poland
关键词
Covering; rough sets; roughness; granularity; distance; SYSTEMS; CLASSIFICATION; GRANULATION; UNCERTAINTY; RULES;
D O I
10.1080/03081079.2015.1086580
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Covering generalized rough set theory is an important extension of classical rough set theory. To characterize a fuzzy set in a given covering approximation space, a pair of fuzzy sets, called covering rough fuzzy lower and upper approximations, were introduced, but they do not describe well how much uncertainty is induced by the granularity of knowledge. In this paper, we first discuss the relationship between uncertainty and granularity of knowledge. Then we examine several commonly used distance measures, and indicate that some of them exhibit some limitations. Next we propose a roughness measure based on Minkowski distance, and examine some important properties of this measure. Finally, an illustrative example is provided to demonstrate the application of the roughness measure to incomplete information systems with fuzzy decision.
引用
收藏
页码:352 / 367
页数:16
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