Some preference involved aggregation models for basic uncertain information using uncertainty transformation
Fecha
2020Versión
Acceso abierto / Sarbide irekia
Tipo
Artículo / Artikulua
Versión
Versión aceptada / Onetsi den bertsioa
Impacto
|
10.3233/JIFS-191106
Resumen
In decision making, very often the data collected are with different extents of uncertainty. The recently introduced concept, Basic Uncertain Information (BUI), serves as one ideal information representation to well model involved uncertainties with different extents. This study discusses some methods of BUI aggregation by proposing some uncertainty transformations for them. Based on some previou ...
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In decision making, very often the data collected are with different extents of uncertainty. The recently introduced concept, Basic Uncertain Information (BUI), serves as one ideal information representation to well model involved uncertainties with different extents. This study discusses some methods of BUI aggregation by proposing some uncertainty transformations for them. Based on some previously obtained results, we at first define Iowa operator with poset valued input vector and inducing vector. The work then defines the concept of uncertain system, on which we can further introduce the multi-layer uncertainty transformation for BUI. Subsequently, we formally introduce MUT-Iowa aggregation procedure, which has good potential to more and wider application areas. A numerical example is also offered along with some simple usage of it in decision making. [--]
Materias
Aggregation function,
BUI aggregation,
Decision making,
Evaluation,
OWA operators,
Uncertain decision making
Editor
IOS Press
Publicado en
Journal of Intelligent and Fuzzy Systems, 2020, 39(1), 325-332
Departamento
Universidad Pública de Navarra. Departamento de Estadística, Informática y Matemáticas /
Nafarroako Unibertsitate Publikoa. Estatistika, Informatika eta Matematika Saila
Versión del editor
Entidades Financiadoras
This work is partly supported under Scientific Research Start-up Foundation with Grant 184080H202B165; partly supported from the Science and Technology Assistance Agency under contract No. APVV-17-0066; partly supported from the project of Grant Agency of the Czech Republic (GACˇ R) no. 18-06915S; partly supported from the Natural Science Foundation of Jiangsu Province (Grants No BK20150870 and No. BK20190695); partly supported from the Jangsu’s Philosophy and Social Science Fund (grant no. 19GLC010).