Linguistic approximation of values close to the gain/loss threshold

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15210%2F17%3A73581327" target="_blank" >RIV/61989592:15210/17:73581327 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Linguistic approximation of values close to the gain/loss threshold

Popis výsledku v původním jazyce

Linguistic approximation (LA) is a natural last step of linguistic fuzzy modelling, providing linguistic labels (with their meaning known to the decision makers and understood well by them). Linguistic approximation techniques are based on approximation and hence the nature of the approximated output of mathematical model can be altered a bit by the application of these methods. LA can be considered beneficial in linguistic fuzzy modelling, as long as the interpretability and understandability of the provided linguistic outputs outweighs the possible loss/distortion of information. In many cases the distortion of information might be small and as such completely acceptable. Recently, however, Stoklasa and Talášek (2015) pointed out that when specific thresholds are of importance in the decision-making situation (e.g. the border between gains and losses), LA can distort the outcome of the decision-making situation by providing a loss label for a gain and vice-versa. In this paper, we investigate the phenomenon under different linguistic scales used for the approximation and provide a thorough discussion of this phenomenon in the context of linguistic approximation.

Název v anglickém jazyce

Linguistic approximation of values close to the gain/loss threshold

Popis výsledku anglicky

Linguistic approximation (LA) is a natural last step of linguistic fuzzy modelling, providing linguistic labels (with their meaning known to the decision makers and understood well by them). Linguistic approximation techniques are based on approximation and hence the nature of the approximated output of mathematical model can be altered a bit by the application of these methods. LA can be considered beneficial in linguistic fuzzy modelling, as long as the interpretability and understandability of the provided linguistic outputs outweighs the possible loss/distortion of information. In many cases the distortion of information might be small and as such completely acceptable. Recently, however, Stoklasa and Talášek (2015) pointed out that when specific thresholds are of importance in the decision-making situation (e.g. the border between gains and losses), LA can distort the outcome of the decision-making situation by providing a loss label for a gain and vice-versa. In this paper, we investigate the phenomenon under different linguistic scales used for the approximation and provide a thorough discussion of this phenomenon in the context of linguistic approximation.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

50202 - Applied Economics, Econometrics

Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

35th International Conference Mathematical Methods in Economics MME 2017 Conference Proceedings

ISBN

978-80-7435-678-0

ISSN

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e-ISSN

neuvedeno

Počet stran výsledku

6

Strana od-do

726-731

Název nakladatele

Gaudeamus

Místo vydání

Hradec Králové

Místo konání akce

Hradec Králové

Datum konání akce

13. 9. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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