Type-1 OWA Unbalanced Fuzzy Linguistic Aggregation Methodology. Application to Eurobonds Credit Risk Evaluation

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.In decision making, a widely used methodology to manage unbalanced fuzzy linguistic information is the linguistic hierarchy (LH), which relies on a linguistic symbolic computational model based on ordinal 2-tuple linguistic representation. However, the ordinal 2-tuple linguistic approach does not exploit all advantages of Zadeh's fuzzy linguistic approach to model uncertainty because the membership function shapes are ignored. Furthermore, the LH methodology is an indirect approach that relies on the uniform distribution of symmetric linguistic assessments. These drawbacks are overcome by applying a fuzzy methodology based on the implementation of the Type-1 Ordered Weighted Average (T1OWA) operator. The T1OWA operator is not a symbolic operator and it allows to directly aggregate membership functions, which in practice means that the T1OWA methodology is suitable for both balanced and unbalanced linguistic contexts and with heterogeneous membership functions. Furthermore, the final output of the T1OWA methodology is always fuzzy and defined in the same domain of the original unbalanced fuzzy linguistic labels, which facilitates its interpretation via a visual joint representation. A case study is presented where the T1OWA operator methodology is used to assess the creditworthiness of European bonds based on real credit risk ratings of individual Eurozone member states modelled as unbalanced fuzzy linguistic labels

Aggregating opinions in non-uniform ordered qualitative scales

Producción CientíficaThis paper introduces a new voting system in the setting of ordered qualitative scales. The process is conducted in a purely ordinal way by considering an ordinal proximity measure that assigns an ordinal degree of proximity to each pair of linguistic terms of the qualitative scale. Once the agents assess the alternatives through the qualitative scale, the alternatives are ranked according to the medians of the ordinal degrees of proximity between the obtained individual assessments and the highest linguistic term of the scale. Since some alternatives may share the same median, an appropriate tie-breaking procedure is introduced. Some properties of the proposed voting system have been provided.Ministerio de Economía, Industria y Competitividad (Project ECO2016-77900-P

Distributed Linguistic Representations in Decision Making: Taxonomy, Key Elements and Applications, and Challenges in Data Science and Explainable Artificial Intelligence

Distributed linguistic representations are powerful tools for modelling the uncertainty and complexity of preference information in linguistic decision making. To provide a comprehensive perspective on the development of distributed linguistic representations in decision making, we present the taxonomy of existing distributed linguistic representations. Then, we review the key elements and applications of distributed linguistic information processing in decision making, including the distance measurement, aggregation methods, distributed linguistic preference relations, and distributed linguistic multiple attribute decision making models. Next, we provide a discussion on ongoing challenges and future research directions from the perspective of data science and explainable artificial intelligence.National Natural Science Foundation of China (NSFC) 71971039 71421001,71910107002,71771037,71874023 71871149Sichuan University sksyl201705 2018hhs-5

Ordinal proximity measures in the context of unbalanced qualitativescales and some applications to consensus and clustering

Producción CientíficaIn this paper, we introduce ordinal proximity measures in the setting of unbalanced qualitative scales by comparing the proximities between linguistic terms without numbers, in a purely ordinal approach. With this new tool, we propose how to measure the consensus in a set of agents when they assess a set of alternatives through an unbalanced qualitative scale. We also introduce an agglomerative hierarchical clustering procedure based on these consensus measures.Ministerio de Economía, Industria y Competitividad (ECO2012-32178)Junta de Castilla y León (programa de apoyo a proyectos de investigación – Ref. VA066U13

On fuzzy-qualitative descriptions and entropy

This paper models the assessments of a group of experts when evaluating different magnitudes, features or objects by using linguistic descriptions. A new general representation of linguistic descriptions is provided by unifying ordinal and fuzzy perspectives. Fuzzy qualitative labels are proposed as a generalization of the concept of qualitative labels over a well-ordered set. A lattice structure is established in the set of fuzzy-qualitative labels to enable the introduction of fuzzy-qualitative descriptions as L-fuzzy sets. A theorem is given that characterizes finite fuzzy partitions using fuzzy-qualitative labels, the cores and supports of which are qualitative labels. This theorem leads to a mathematical justification for commonly-used fuzzy partitions of real intervals via trapezoidal fuzzy sets. The information of a fuzzy-qualitative label is defined using a measure of specificity, in order to introduce the entropy of fuzzy-qualitative descriptions. (C) 2016 Elsevier Inc. All rights reserved.Peer ReviewedPostprint (author's final draft

Perceptual maps to aggregate information from decision makers

Understanding different perceptions of human being when using linguistic terms is a crucial issue in human-machine interaction. In this paper, we propose the concept of perceptual maps to model human opinions in a group decision-making context. The proposed approach considers a multi-granular structure using unbalanced hesitant linguistic term sets. An illustrative case is presented in the location decisions made by multinationals enterprises of the energy sector within the European smart city context.This research was supported partly by the INVITE research project (TIN2016- 80049-C2-1-R and TIN2016-80049-C2-2-R), funded by the Spanish Ministry of Science and Information Technology and the European Union Horizon 2020 Research and Innovation Programme, under the grant agreement No 731297.Postprint (published version

A Review on Information Accessing Systems Based on Fuzzy Linguistic Modelling

This paper presents a survey of some fuzzy linguistic information access systems. The review shows information retrieval systems, filtering systems, recommender systems, and web quality evaluation tools, which are based on tools of fuzzy linguistic modelling. The fuzzy linguistic modelling allows us to represent and manage the subjectivity, vagueness and imprecision that is intrinsic and characteristic of the processes of information searching, and, in such a way, the developed systems allow users the access to quality information in a flexible and user-adapted way.European Union (EU) TIN2007-61079 PET2007-0460Ministry of Public Works 90/07Excellence Andalusian Project TIC529

A Linguistic Group Best–Worst Method for Measuring Good Governance in the Third Sector: A Spanish Case Study

The need of Non-profit Organizations (NPOs) of generating trust and credibility, to their stakeholders by an efficient management of their resources, lead them to openly show that they develop adequate good governance practices. But this is not a simple task and few research has been done on measuring methods of good governance in this field; without achieving an agreement about the best procedure. This paper aims at facilitating the measurement of good governance practices in NPOs by a fuzzy linguistic consensus-based group multi-criteria decision-making (MCGDM) model that will provide agreed and easy-understanding weights for a list of indicators proposed by the stakeholders and entities in such good governance practices. To do that, a linguistic 2-tuple BWM method with a consensus reaching process (CRP) will be developed and then applied to a real-world case in Spain, in which a group of experts from significant Spanish NPOs will assess the list of indicators proposed by the most representative entities (the alliance between the non-governmental organizations (NGO) Platform for Social Action, and the NGO Coordinator for Development (CONGDE) to obtain a prioritization of such indicators for measuring the good governance practices in Spanish NPOs.Ministerio de Economía y Competitividad (Gobierno de España) a través del Proyecto de Investigación Nacional PGC2018-099402-B-I00, la Beca Posdoctoral Ramón y Cajal (RYC-2017-21978) y el proyecto FEDER-UJA 1380637 y ERDF