Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Electrostatic precipitator problem"'
Publikováno v:
IEEE Access, Vol 12, Pp 86144-86159 (2024)
Expensive optimization problems are characterized by the significant amount of time and resources needed to determine the quality of potential solutions. This poses severe limitations for the application of metaheuristic optimization methods, such as
Externí odkaz:
https://doaj.org/article/9210c87c494b4ecaa923e4737c4d1c01
Akademický článek
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Publikováno v:
IEEE Transactions on Industry Applications. May/Jun2002, Vol. 38 Issue 3, p858. 8p. 4 Black and White Photographs, 2 Diagrams, 5 Graphs.
Publikováno v:
International Journal of Numerical Modelling. Jan/Feb97, Vol. 10 Issue 1, p47-56. 10p. 1 Diagram.
Publikováno v:
GECCO
Real-world problems such as computational fluid dynamics simulations and finite element analyses are computationally expensive. A standard approach to mitigating the high computational expense is Surrogate-Based Optimization (SBO). Yet, due to the hi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f3b87685b0151e225a7d2bd6cf0e8ae8
https://cos.bibl.th-koeln.de/files/906/rehb20bcos.pdf
https://cos.bibl.th-koeln.de/files/906/rehb20bcos.pdf
Publikováno v:
GECCO (Companion)
We propose a hybridization approach called Regularized-Surrogate- Optimization (RSO) aimed at overcoming difficulties related to high- dimensionality. It combines standard Kriging-based SMBO with regularization techniques. The employed regularization
Publikováno v:
GECCO
The availability of several CPU cores on current computers enables parallelization and increases the computational power significantly. Optimization algorithms have to be adapted to exploit these highly parallelized systems and evaluate multiple cand
Autor:
Lawless, P.A.
Publikováno v:
Conference Record of the IEEE Industry Applications Society Annual Meeting; 1989, p1999-1999, 1p
Autor:
Lawless, P.A.
Publikováno v:
Conference Record of the 1988 IEEE Industry Applications Society Annual Meeting; 1988, p1692-1692, 1p
Autor:
Frederik Rehbach
This book presents a solution to the challenging issue of optimizing expensive-to-evaluate industrial problems such as the hyperparameter tuning of machine learning models. The approach combines two well-established concepts, Surrogate-Based Optimiza