Bustince Sola, Humberto

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https://academica-e.unavarra.es/handle/2454/48764

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Bustince Sola

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Humberto

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Estadística, Informática y Matemáticas

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ISC. Institute of Smart Cities

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0000-0002-1279-6195

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88384

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278

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2021 - 20222
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Author: Chen, Zhen-Song × Subject: Evaluation ×

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    PublicationOpen Access
    Some bipolar-preferences-involved aggregation methods for a sequence of OWA weight vectors
    (Springer, 2021) Jin, LeSheng; Yager, Ronald R.; Chen, Zhen-Song; Špirková, Jana; Paternain Dallo, Daniel; Mesiar, Radko; Bustince Sola, Humberto; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
    The ordered weighted averaging (OWA) operator and its associated weight vectors have been both theoretically and practically verified to be powerful and effective in modeling the optimism/pessimism preference of decision makers. When several different OWA weight vectors are offered, it is necessary to develop certain techniques to aggregate them into one OWA weight vector. This study firstly details several motivating examples to show the necessity and usefulness of merging those OWA weight vectors. Then, by applying the general method for aggregating OWA operators proposed in a recent literature, we specifically elaborate the use of OWA aggregation to merge OWA weight vectors themselves. Furthermore, we generalize the normal preference degree in the unit interval into a preference sequence and introduce subsequently the preference aggregation for OWA weight vectors with given preference sequences. Detailed steps in related aggregation procedures and corresponding numerical examples are also provided in the current study.
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    PublicationOpen Access
    Unsymmetrical basic uncertain information with some decision-making methods
    (IOS Press, 2022) Jin, LeSheng; Yager, Ronald R.; Chen, Zhen-Song; Mesiar, Radko; Bustince Sola, Humberto; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
    Motivated by a specific decision-making situation, this work proposes the concept and definition of unsymmetrical basic uncertain information which is a further generalization of basic uncertain information and can model uncertainties in some new decision-making situations. We show that unsymmetrical basic uncertain information in some sense can model linguistic hedges such as 'at least' and 'at most'. Formative weighted arithmetic means and induced aggregations are defined for the proposed concept. Rules-based decision making and semi-copula based integral for this concept with some numerical examples are also presented.