On discrete preference structures
Technologies for constructing intelligent systems
Aggregation techniques for statistical confidentiality
Aggregation operators
Ordinal decomposability and fuzzy connectives
Fuzzy Sets and Systems - Theme: Multicriteria decision
Disclosure risk assessment in statistical microdata protection via advanced record linkage
Statistics and Computing
A Learning Algorithm for Level Sets Weights in Weighted Level-based Averaging Method
Fuzzy Optimization and Decision Making
Induced uncertain linguistic OWA operators applied to group decision making
Information Fusion
The solution equivalence of minimax disparity and minimum variance problems for OWA operators
International Journal of Approximate Reasoning
Information Sciences: an International Journal
Discrete t-norms and operations on extended multisets
Fuzzy Sets and Systems
Parameterized defuzzification with continuous weighted quasi-arithmetic means - An extension
Information Sciences: an International Journal
Fuzzy Sets and Systems
Fuzzy Optimization and Decision Making
On two types of discrete implications
International Journal of Approximate Reasoning
The orness measures for two compound quasi-arithmetic mean aggregation operators
International Journal of Approximate Reasoning
Smooth t-subnorms on finite scales
Fuzzy Sets and Systems
Aggregation of subjective evaluations based on discrete fuzzy numbers
Fuzzy Sets and Systems
Group decision making based on induced uncertain linguistic OWA operators
Decision Support Systems
A new linguistic computational model based on discrete fuzzy numbers for computing with words
Information Sciences: an International Journal
| Hi-index | 0.00 |
In many fuzzy systems applications, values to be aggregated are of a qualitative nature. In that case, if one wants to compute some type of average, the most common procedure is to perform a numerical interpretation of the values, and then apply one of the well-known (the most suitable) numerical aggregation operators. However, if one wants to stick to a purely qualitative setting, choices are reduced to either weighted versions of max-min combinations or to a few existing proposals of qualitative versions of ordered weighted average (OWA) operators. In this paper, we explore the feasibility of defining a qualitative counterpart of the weighted mean operator without having to use necessarily any numerical interpretation of the values. We propose a method to average qualitative values, belonging to a (finite) ordinal scale, weighted with natural numbers, and based on the use of finite t-norms and t-conorms defined on the scale of values. Extensions of the method for other OWA-like and Choquet integral-type aggregations are also considered