In this paper, we present and apply a new aggregation principle for hesitant fuzzy elements (HFEs). First, we introduce a membership uncertainty index of the HFEs. Then we present a new aggregation principle for aggregating hesitant fuzzy elements, which can effectively reduce the computational complexity specific to the conventional aggregation principle. By the virtue of the proposed aggregation principle, the number of terms (values) in the aggregation result is significantly reduced. Furthermore, a t-test confirms that the scores associated with the results of the aggregation under conventional and new principles have no significant difference. Furthermore, a series of simulations are provided to demonstrate the feasibility and validity of the proposed aggregation principle.
Keywords: Hesitant fuzzy set; Membership uncertainty; Aggregation principle; Aggregation operator.
Impact Factor: 2.947, 2014
SCImago Journal Rank (SJR): 1.977
Source Normalized Impact per Paper (SNIP): 2.603
© 2015 Elsevier
Mu, Z.; Zeng, Sh.; Baležentis, T. 2015. A novel aggregation principle for hesitant fuzzy elements, In Knowledge-Based Systems 84:134-143. ISSN: 0950-7051. doi:10.1016/j.knosys.2015.04.008. [Abstracts in Artificial Intelligence, CompuScience, Computer Literature Index, Current Contents, Current Contents/CompuMath, INSPEC Computer and Control Abstracts, Research Alert, SCISEARCH, Science Citation Index, Zentralblatt MATH, PsycINFO, Scopus].