2026-05-05T21:37:05Zhttps://uvadoc.uva.es/oai/requestoai:uvadoc.uva.es:10324/214952021-06-23T10:05:50Zcom_10324_1146com_10324_931com_10324_894col_10324_1262
UVaDOC
author
Llamazares Rodríguez, Bonifacio
2016-12-09T10:28:49Z
2016-12-09T10:28:49Z
2016
International Journal of Intelligent Systems, 2016, vol. 31, p. 827–851
0884-8173
http://uvadoc.uva.es/handle/10324/21495
10.1002/int.21806
827
851
International Journal of Intelligent Systems
31
Weighted ordered weighted averaging (WOWA) and semiuninorm-based ordered weighted averaging (SUOWA) operators are two families of aggregation functions that simultaneously generalize weighted means and OWA operators. Both families can be obtained by using the Choquet integral with respect to normalized capacities. Therefore, they are continuous, monotonic, idempotent, compensative, and homogeneous of degree 1 functions. Although both families fulfill good properties, there are situations where their behavior is quite different. The aim of this paper is to analyze both families of functions regarding some simple cases of weighting vectors, the capacities from which they are building, the weights affecting the components of each vector, and the values they return.
eng
Attribution-NonCommercial-NoDerivatives 4.0 International
Matemáticas
Operadores, Teoría de
A Behavioral Analysis of WOWA and SUOWA Operators
info:eu-repo/semantics/article
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