Aggregation functions: Construction methods, conjunctive, disjunctive and mixed classes

Abstract

a b s t r a c tIn this second part of our state-of-the-art overview on aggregation theory, based again on our recent monograph on aggregation functions, we focus on several construction methods for aggregation functions and on special classes of aggregation functions, covering the well-known conjunctive, disjunctive, and mixed aggregation functions. Some fields of applications are included.

CoTO: A Novel Approach for Fuzzy Aggregation of Semantic Similarity Measures

“…In the field of semantic similarity measurement, aggregation functions are generally defined and used [15]. 1 We will investigate approaches using a larger amount of linguistic terms in the future It is necessary to remark that aggregation is a very extensive research field in which numerous types of aggregation functions or operators exist.…”

Dual hesitant fuzzy power aggregation operators based on Archimedean t-conorm and t-norm and their application to multiple attribute group decision making

“…The investigation on information aggregation has received surprisingly extensive attention from practitioners and researchers due to its practical and academic significance [13][14][15][16]. Based on Archimedean tconorm and t-norm [17,18], and the aggregation functions for the classical FSs [19,20], Beliakov et al [21] gave some operations about IFSs, proposed two general concepts for constructing other types of aggregation operators for IFSs extending the existing methods and showed that the operators obtained by using the Łukasiewicz t-norm are consistent with the ones on ordinary FSs. Xia and Xu [22] introduced a series of aggregation operators for hesitant fuzzy information and discussed the relationships among them.…”

Architecture for Business Intelligence Design on the IT Service Management Scope

“…Based on this strength the business analyst can builds a semantic model and then they can use the inference capability of the logical platform to facilitate assessment on any situation, decision making or knowledge discovery. In [21] appears an state-of-theart overview on aggregation theory based on fuzzy logic, also in [22][23][24] is showed the aggregation methods approach. We propose in this research the use the aforementioned methods to define the indicators in the BSC cascade based on best practice frameworks for IT service management such as COBIT and ITIL.…”