A1 Journal article (refereed), original research

Executive summaries of uncertain values close to the gain/loss threshold – linguistic modelling perspective


Publication Details
Authors: Stoklasa Jan, Talášek Tomáš, Stoklasová Jana
Publisher: Elsevier
Publication year: 2020
Language: English
Related Journal or Series Information: Expert Systems with Applications
Journal acronym: ESWA
Volume number: 145
ISSN: 0957-4174
eISSN: 1873-6793
JUFO-Level of this publication: 1
Open Access: Not an Open Access publication

Abstract

In this paper we propose a novel method for the assessment of linguistic
approximation of fuzzy outputs of decision-support and evaluation
models in the presence of thresholds. The method provides graphical and
numerical summaries of performance of different distance/similarity
measures in combination with various linguistic scales in the process of
assigning linguistic labels to the outputs of expert systems and
decision-support models. We assume the existence of a specific threshold
on the output scale that splits the outputs in two categories, i.e.
gains/losses, acceptable/unacceptable values, better/worse than average
values etc. This way a framing of the outputs can be obtained by
labelling them linguistically. We consider numerical outputs in monetary
units and assume zero to be the threshold value, splitting the universe
into gains and losses. Based on a numerical analysis and yet without
the knowledge of the most fitting linguistic label, the proposed
analytical method is able to identify the cases where a clearly
incorrect label is assigned (a loss label for a gain an/or vice versa)
and hence the combinations of linguistic scales and distance/similarity
measures of fuzzy numbers not to be used for the given purpose. We can
also analyze specific features of some similarity/distance and
linguistic scale combinations. The proposed method and its outputs is
intended for the design of such expert systems and decision-support
models, where a linguistic level ofccommunicating the results to the
users of these models is of importance, e.g., for the creation of
executive summaries of outputs of mathematical models and results of
financial data analyses. The method brings together the mathematical
analysis of the linguistic approximation tools and the behavioral aspect
of framing of the outputs e.g., as gains or losses prior to the final
decision-making step. This way it provides much need guidance for the
selection of reasonable distance/similarity measures of fuzzy numbers
and reasonable linguistic scale for linguistic approximation. As such it
is a useful tool for the design of system-user interfaces including a
linguistic level of description.


Last updated on 2020-25-03 at 14:18