Surrogate Model for Continuous and Discrete Genetic Optimization Based on RBF Networks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F10%3A10049939" target="_blank" >RIV/00216208:11320/10:10049939 - 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

Surrogate Model for Continuous and Discrete Genetic Optimization Based on RBF Networks

Popis výsledku v původním jazyce

Surrogate modelling has become a successful method improving the optimization of costly objective functions. It brings less accurate, but much faster means of evaluating candidate solutions. This paper describes a model based on radial basis function networks which takes into account both continuous and discrete variables. It shows the applicability of our surrogate model to the optimization of empirical objective functions for which mixing of discrete and continuous dimensions is typical. Results of testing with a genetic algorithm confirm considerably faster convergence in terms of the number of the original empirical fitness evaluations.

Název v anglickém jazyce

Surrogate Model for Continuous and Discrete Genetic Optimization Based on RBF Networks

Popis výsledku anglicky

Surrogate modelling has become a successful method improving the optimization of costly objective functions. It brings less accurate, but much faster means of evaluating candidate solutions. This paper describes a model based on radial basis function networks which takes into account both continuous and discrete variables. It shows the applicability of our surrogate model to the optimization of empirical objective functions for which mixing of discrete and continuous dimensions is typical. Results of testing with a genetic algorithm confirm considerably faster convergence in terms of the number of the original empirical fitness evaluations.

Druh

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

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/GD201%2F09%2FH057" target="_blank" >GD201/09/H057: Res Informatica</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2010

Kód důvěrnosti údajů

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

Název periodika

Lecture Notes in Computer Science

ISSN

0302-9743

e-ISSN

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Svazek periodika

2010

Číslo periodika v rámci svazku

6283

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

8

Strana od-do

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Kód UT WoS článku

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EID výsledku v databázi Scopus

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