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• W2953612138 abstract "Surrogate modeling is an increasingly popular tool for engineering design as it enables to model the performance of very complex systems with a limited computational cost. A large number of techniques exists for the surrogate modeling of continuous functions, however, only a very few methods for the surrogate modeling of mixed continuous/discrete functions have been developed. In this chapter, existing adaptations and variants of Gaussian process-based surrogate modeling techniques for mixed continuous/discrete variables are described, discussed and compared on several analytical test-cases and aerospace design problems." @default.
• W2953612138 created "2019-07-12" @default.
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• W2953612138 date "2019-06-02" @default.
• W2953612138 modified "2023-09-25" @default.
• W2953612138 title "Overview and Comparison of Gaussian Process-Based Surrogate Models for Mixed Continuous and Discrete Variables: Application on Aerospace Design Problems" @default.
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• W2953612138 doi "https://doi.org/10.1007/978-3-030-18764-4_9" @default.
• W2953612138 hasPublicationYear "2019" @default.
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