Optimizing aerodynamic shape of benchmark problems using an improved Gaussian process regression algorithm
The current challenges encountered in Surrogate-Based Optimization (SBO) primarily stem from the substantial number of function calls essential for accurate evaluations. A promising approach to alleviate this problem is to leverage Gaussian Process Regression (GPR) models integrated with Automatic K...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Engineering Applications of Computational Fluid Mechanics |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/19942060.2025.2456500 |
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