An entropy measure definition for finite interval-valued hesitant fuzzy sets

被引:45
|
作者
Quiros, Pelayo [1 ]
Alonso, Pedro [1 ]
Bustince, Humberto [2 ]
Diaz, Irene [3 ]
Montes, Susana [4 ]
机构
[1] Univ Oviedo, Fac Sci, Dept Math, E-33071 Oviedo, Spain
[2] Univ Publ Navarra, Dept Comp Sci & Artificial Intelligence, Pamplona 31006, Spain
[3] Univ Oviedo, Dept Comp Sci, Fac Sci, E-33071 Oviedo, Spain
[4] Univ Oviedo, Univ Tech Sch Ind Engn, Dept Stat & OR, Viesques Campus, Gijon 33203, Spain
关键词
Fuzzy sets; Hesitant fuzzy sets; Interval-valued hesitant fuzzy sets; Entropy; Fuzziness; Lack of knowledge; Hesitance; RESTRICTED EQUIVALENCE FUNCTIONS; MULTICRITERIA DECISION-MAKING; LINGUISTIC TERM SETS; AGGREGATION;
D O I
10.1016/j.knosys.2015.04.005
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this work, a definition of entropy is studied in an interval-valued hesitant fuzzy environment, instead of the classical fuzzy logic or the interval-valued one. As the properties of this kind of sets are more complex, the entropy is built by three different functions, where each one represents a different measure: fuzziness, lack of knowledge and hesitance. Using all, an entropy measure for interval-valued hesitant fuzzy sets is obtained, quantifying various types of uncertainty. From this definition, several results have been developed for each mapping that shapes the entropy measure in order to get such functions with ease, and as a consequence, allowing to obtain this new entropy in a simpler way. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:121 / 133
页数:13
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