Assessing the Suitability of Surrogate Models in Evolutionary Optimization

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F11%3A00368902" target="_blank" >RIV/67985807:_____/11:00368902 - 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

Assessing the Suitability of Surrogate Models in Evolutionary Optimization

Popis výsledku v původním jazyce

The paper deals with the application of evolutionary algorithms to black-box optimization, frequently encountered in biology, chemistry and engineering. In those areas, however, the evaluation of the black-box fitness is often costly and time-consuming.Such a situation is usually tackled by evaluating the original fitness only sometimes, and evaluating its appropriate response-surface model otherwise, called surrogate model of the fitness. Several kinds of models have been successful in surrogate modelling, and a variety of models of each kind can be obtained through parametrization. Therefore, real-world applications of surrogate modelling entail the problem of assessing the suitability of different models for the optimization task being solved. Thepresent paper attempts to systematically inves- tigate this problem. It surveys available methods to assess model suitability and reports the incorporation of several such methods in our recently proposed approach to surrogate modelling b

Název v anglickém jazyce

Assessing the Suitability of Surrogate Models in Evolutionary Optimization

Popis výsledku anglicky

The paper deals with the application of evolutionary algorithms to black-box optimization, frequently encountered in biology, chemistry and engineering. In those areas, however, the evaluation of the black-box fitness is often costly and time-consuming.Such a situation is usually tackled by evaluating the original fitness only sometimes, and evaluating its appropriate response-surface model otherwise, called surrogate model of the fitness. Several kinds of models have been successful in surrogate modelling, and a variety of models of each kind can be obtained through parametrization. Therefore, real-world applications of surrogate modelling entail the problem of assessing the suitability of different models for the optimization task being solved. Thepresent paper attempts to systematically inves- tigate this problem. It surveys available methods to assess model suitability and reports the incorporation of several such methods in our recently proposed approach to surrogate modelling b

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/GAP202%2F11%2F1368" target="_blank" >GAP202/11/1368: Učení funkcionálních vztahů z vysoce dimenzionálních dat</a><br>

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2011

Kód důvěrnosti údajů

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

Název statě ve sborníku

Information Technologies - Applications and Theory

ISBN

978-80-89557-02-8

ISSN

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e-ISSN

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Počet stran výsledku

8

Strana od-do

31-38

Název nakladatele

PONT s.r.o.

Místo vydání

Seňa

Místo konání akce

Ždiar

Datum konání akce

17. 9. 2011

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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