An improved high-dimensional Bayesian optimization algorithm

The Bayesian Optimization Algorithm, as an effective approach to addressing non-linear global optimization problems, is widely embraced in a myriad of machine learning application domains. With the development of big data, the presence of computational and statistical challenges in high-dimensional...

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Veröffentlicht in:	Applied intelligence (Dordrecht, Netherlands) Jg. 55; H. 13; S. 915
Hauptverfasser:	Guan, Juan, Wang, Yanhua
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.08.2025 Springer Nature B.V
Schlagworte:	Algorithms Artificial Intelligence Bayesian analysis Clustering Computer Science Datasets Decomposition Design optimization Global optimization Machine learning Machines Manufacturing Mechanical Engineering Methods Optimization algorithms Principal components analysis Processes KPCA High-dimensional Bayesian optimization MIMIC algorithm Variable interaction
ISSN:	0924-669X, 1573-7497
Online-Zugang:	Volltext
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