Multi-objective optimization of function approximation using fuzzy rules

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F26867184%3A_____%2F13%3A004" target="_blank" >RIV/26867184:_____/13:004 - 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

Multi-objective optimization of function approximation using fuzzy rules

Popis výsledku v původním jazyce

The paper describes the development and achieved results using a fuzzy approximation of a real function applies to macroeconomic research. The fuzzy approximation utilizes multi-objective optimization to improve the achieved results. The accuracy of theapproximated function and interpretability index of the fuzzy sets are utilized for multi-objective optimization by employing the Mamdani and Assilian method. A simple interpretability index that evaluates the distinguishability and coverage of the fuzzysets is introduced and implemented in the optimizing framework. The rule base is derived in accordance with the course of the approximated function. This function is specified in the form of discrete points, the density of which can vary. The optimizingcriterion minimizes the weighted sum of the accuracy of the approximated function and the interpretability index. A design approach is proven using macroeconomic research, investigating relations between total greenhouse gas emissions an

Název v anglickém jazyce

Multi-objective optimization of function approximation using fuzzy rules

Popis výsledku anglicky

The paper describes the development and achieved results using a fuzzy approximation of a real function applies to macroeconomic research. The fuzzy approximation utilizes multi-objective optimization to improve the achieved results. The accuracy of theapproximated function and interpretability index of the fuzzy sets are utilized for multi-objective optimization by employing the Mamdani and Assilian method. A simple interpretability index that evaluates the distinguishability and coverage of the fuzzysets is introduced and implemented in the optimizing framework. The rule base is derived in accordance with the course of the approximated function. This function is specified in the form of discrete points, the density of which can vary. The optimizingcriterion minimizes the weighted sum of the accuracy of the approximated function and the interpretability index. A design approach is proven using macroeconomic research, investigating relations between total greenhouse gas emissions an

Druh

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

CEP obor

AH - Ekonomie

OECD FORD obor

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Projekt

<a href="/cs/project/GAP403%2F12%2F1811" target="_blank" >GAP403/12/1811: Vývoj nekonvenčních metod manažerského rozhodování v oblasti podnikové ekonomiky a veřejné ekonomie</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2013

Kód důvěrnosti údajů

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

Název periodika

ECON - Journal of Economics, Management and Business

ISSN

1803-3865

e-ISSN

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Svazek periodika

23

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

12

Strana od-do

3-14

Kód UT WoS článku

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EID výsledku v databázi Scopus

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