Fuzzy Methods of Multiple-Criteria Evaluation and Their Software Implementation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F12%3A33141812" target="_blank" >RIV/61989592:15310/12:33141812 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.4018/978-1-61350-429-1.ch021" target="_blank" >http://dx.doi.org/10.4018/978-1-61350-429-1.ch021</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.4018/978-1-61350-429-1.ch021" target="_blank" >10.4018/978-1-61350-429-1.ch021</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Fuzzy Methods of Multiple-Criteria Evaluation and Their Software Implementation

Popis výsledku v původním jazyce

This chapter describes a system of fuzzy methods designed to solve a broad range of problems in multiple-criteria evaluation, and also their software implementation, FuzzME. A feature common to all the presented methods is the type of evaluation, well suited to the paradigm of fuzzy set theory. All evaluations take on the form of fuzzy numbers, expressing the extent to which goals of evaluation are fulfilled. The system of fuzzy methods is conceived to allow for different types of interaction among criteria of evaluation. Under no interaction, the fuzzy weighted average, fuzzy OWA operator, or WOWA operator are used to aggregate partial evaluations (depending on the evaluator's requirements regarding type of evaluation). If interactions appear as redundancy or complementarity, the fuzzified discrete Choquet integral is the appropriate aggregation operator. Under more complex interactions, the aggregation function is defined through an expertly set base of fuzzy rules.

Název v anglickém jazyce

Fuzzy Methods of Multiple-Criteria Evaluation and Their Software Implementation

Popis výsledku anglicky

This chapter describes a system of fuzzy methods designed to solve a broad range of problems in multiple-criteria evaluation, and also their software implementation, FuzzME. A feature common to all the presented methods is the type of evaluation, well suited to the paradigm of fuzzy set theory. All evaluations take on the form of fuzzy numbers, expressing the extent to which goals of evaluation are fulfilled. The system of fuzzy methods is conceived to allow for different types of interaction among criteria of evaluation. Under no interaction, the fuzzy weighted average, fuzzy OWA operator, or WOWA operator are used to aggregate partial evaluations (depending on the evaluator's requirements regarding type of evaluation). If interactions appear as redundancy or complementarity, the fuzzified discrete Choquet integral is the appropriate aggregation operator. Under more complex interactions, the aggregation function is defined through an expertly set base of fuzzy rules.

Druh

C - Kapitola v odborné knize

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2012

Kód důvěrnosti údajů

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

Název knihy nebo sborníku

Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition: Advancing Technologies

ISBN

978-1-61350-429-1

Počet stran výsledku

24

Strana od-do

388-411

Počet stran knihy

784

Název nakladatele

IGI Global

Místo vydání

Hershey, USA

Kód UT WoS kapitoly

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