Open AccessAggregation Operators in Hesitant Fuzzy Set for Decision Making
Author(s) -
Roopa Ravindranath,
Gowri Ganesh N.S,
A Mummoorthy,
A Gayathri
Publication year - 2021
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.d6586.1110421
Subject(s) - fuzzy set , extension (predicate logic) , fuzzy logic , type 2 fuzzy sets and systems , fuzzy set operations , computer science , element (criminal law) , set (abstract data type) , fuzzy classification , range (aeronautics) , data mining , fuzzy number , artificial intelligence , mathematics , engineering , aerospace engineering , political science , law , programming language
Uncertainty is prevalent in a wide range of real-world issues. The fuzzy sets, vague sets or intuitionistic fuzzy sets are widely used in recent years for decision making and various analysis where uncertainty is predominant. An extension of fuzzy sets is Hesitant Fuzzy Sets, which deals with ambiguous situations that arise when determining an element's membership degree in a set. Researchers have defined various ideas, extensions, aggregation operators, and measurements to deal with reluctant information as a result of this new approach. Machine leaning algorithms are also exploiting hesitant fuzzy sets for better decision making.