Some interesting properties of the fuzzy linguistic model based on discrete fuzzy numbers to manage hesitant fuzzy linguistic information |
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| Affiliation: | 1. Department of Mathematics and Computer Science, University of the Balearic Islands, Ctra. de Valldemossa, Km.7.5, 07122 Palma de Mallorca, Spain;2. Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain;1. Department of Mathematics and Computer Science, University of the Balearic Islands, 07122 Palma, Balearic Islands, Spain;2. Balearic Islands Health Research Institute (IdISBa), 07010 Palma, Spain;3. Departamento de Ciencias de la Computación, Arquitectura de Computadores, Lenguajes y Sistemas Informáticos y Estadística e Investigación Operativa, Universidad Rey Juan Carlos, 28933 Móstoles, Madrid, Spain;1. Department of Anesthesiology and Critical Care Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia;2. ChenMed, Miami, Fla;3. Pharmacy Procurement & Formulary Services, Department of Pharmacy and Therapeutics, The Geisinger Health System, Danville, Pa;4. Critical Care Medicine, The Geisinger Health System, Danville, Pa;5. Department of Medicine, Temple University School of Medicine, Philadelphia, Pa;1. School of Electrical Engineering and Computer Science, University of Bradford, Bradford, UK;2. Manchester Royal Eye Hospital, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester M13 9WL, UK |
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| Abstract: | The management of hesitant fuzzy information is a topic of special interest in fuzzy decision making. In this paper, we focus on the use and properties of the fuzzy linguistic modelling based on discrete fuzzy numbers to manage hesitant fuzzy linguistic information. Among these properties, we can highlight the existence of aggregation functions with no need of transformations or the possibility of a greater flexibilization of the opinions of the experts, even using different linguistic chains (multigranularity). Furthermore, based on these properties we perform a comparison between this model and the one based on hesitant fuzzy linguistic term sets, showing the advantages of the former with respect to the latter. Finally, a fuzzy decision making model based on discrete fuzzy numbers is proposed. |
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| Keywords: | Decision support systems Discrete fuzzy numbers Subjective evaluation Hesitant fuzzy linguistic term set Multiple-criteria decision making problem |
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