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KOBLIHA, M. SCHWARZ, J. OČENÁŠEK, J.
Originální název
Bayesian Optimization Algorithms for Dynamic Problems
Typ
článek ve sborníku mimo WoS a Scopus
Jazyk
angličtina
Originální abstrakt
This paper is an experimental study investigating the capability of Bayesian optimization algorithms to solve dynamic problems. We tested the performance of two variants of Bayesian optimization algorithms - Mixed continuous-discrete Bayesian Optimization Algorithm (MBOA), Adaptive Mixed Bayesian Optimization Algorithm (AMBOA) - and new proposed modifications with embedded Sentinels concept and Hypervariance. We have compared the performance of these variants on a simple dynamic problem - a time-varying function with predefined parameters. The experimental results confirmed the benefit of Sentinels concept and Hypervariance embedded into MBOA algorithm for tracking a moving optimum.
Klíčová slova
BOA algorithm, dynamic problem, optimalization
Autoři
KOBLIHA, M.; SCHWARZ, J.; OČENÁŠEK, J.
Rok RIV
2006
Vydáno
8. 3. 2006
Nakladatel
Springer Verlag
Místo
Budapest
ISBN
3-540-33237-5
Kniha
Applications of Evolutionary Computing
ISSN
0302-9743
Periodikum
Lecture Notes in Computer Science
Ročník
Číslo
3907
Stát
Spolková republika Německo
Strany od
800
Strany do
804
Strany počet
5
BibTex
@inproceedings{BUT22416, author="Miloš {Kobliha} and Josef {Schwarz} and Jiří {Očenášek}", title="Bayesian Optimization Algorithms for Dynamic Problems", booktitle="Applications of Evolutionary Computing", year="2006", journal="Lecture Notes in Computer Science", volume="2006", number="3907", pages="800--804", publisher="Springer Verlag", address="Budapest", isbn="3-540-33237-5", issn="0302-9743" }