Several Results on Set-Valued Possibilistic Distributions

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F15%3A00444153" target="_blank" >RIV/67985807:_____/15:00444153 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.14736/kyb-2015-3-0391" target="_blank" >http://dx.doi.org/10.14736/kyb-2015-3-0391</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.14736/kyb-2015-3-0391" target="_blank" >10.14736/kyb-2015-3-0391</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Several Results on Set-Valued Possibilistic Distributions

Popis výsledku v původním jazyce

When proposing and processing uncertainty decision-making algorithms of various kinds and purposes, we more and more often meet probability distributions ascribing non-numerical uncertainty degrees to random events. The reason is that we have to processsystems of uncertainties for which the classical conditions like sigma-additivity or linear ordering of values are too restrictive to define sufficiently closely the nature of uncertainty we would like to specify and process. In cases of non-numerical uncertainty degrees, at least the following two criteria may be considered. The first criterion should be systems with rather complicated, but sophisticated and nontrivially formally analyzable uncertainty degrees, e. g., uncertainties supported by some algebras or partially ordered structures. Contrarily, we may consider easier relations, which are non-numerical but interpretable on the intuitive level. Well-known examples of such structures are set-valued possibilistic measures. Some spe

Název v anglickém jazyce

Several Results on Set-Valued Possibilistic Distributions

Popis výsledku anglicky

When proposing and processing uncertainty decision-making algorithms of various kinds and purposes, we more and more often meet probability distributions ascribing non-numerical uncertainty degrees to random events. The reason is that we have to processsystems of uncertainties for which the classical conditions like sigma-additivity or linear ordering of values are too restrictive to define sufficiently closely the nature of uncertainty we would like to specify and process. In cases of non-numerical uncertainty degrees, at least the following two criteria may be considered. The first criterion should be systems with rather complicated, but sophisticated and nontrivially formally analyzable uncertainty degrees, e. g., uncertainties supported by some algebras or partially ordered structures. Contrarily, we may consider easier relations, which are non-numerical but interpretable on the intuitive level. Well-known examples of such structures are set-valued possibilistic measures. Some spe

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

BA - Obecná matematika

OECD FORD obor

—

Projekt

<a href="/cs/project/GAP202%2F10%2F1826" target="_blank" >GAP202/10/1826: Matematická fuzzy logika v informatice</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název periodika

Kybernetika

ISSN

0023-5954

e-ISSN

—

Svazek periodika

51

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

17

Strana od-do

391-407

Kód UT WoS článku

000361266300002

EID výsledku v databázi Scopus

2-s2.0-84940036692