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An adaptive RBF-HDMR modeling approach under limited computational budget
| Content Provider | Semantic Scholar |
|---|---|
| Author | Liu, Haitao Hervás, J. Ong, Yew-Soon Cai, Jianfei Wang, Yi |
| Copyright Year | 2018 |
| Abstract | The metamodel-based high-dimensional model representation (e.g., RBF-HDMR) has recently been proven to be very promising for modeling high dimensional functions. A frequently encountered scenario in practical engineering problems is the need of building accurate models under limited computational budget. In this context, the original RBF-HDMR approach may be intractable due to the independent and successive treatment of the component functions, which translates in a lack of knowledge on when the modeling process will stop and how many points (simulations) it will cost. This article proposes an adaptive and tractable RBF-HDMR (ARBF-HDMR) modeling framework. Given a total of Nmax points, it first uses Nini points to build an initial RBF-HDMR model for capturing the characteristics of the target function f, and then keeps adaptively identifying, sampling and modeling the potential cuts with the remaining Nmax − Nini points. For the second-order ARBF-HDMR, Nini ∈ [2n + 2,2n2 + 2] not only depends on the dimensionality n but also on the characteristics of f. Numerical results on nine cases with up to 30 dimensions reveal that the proposed approach provides more accurate predictions than the original RBF-HDMR with the same computational budget, and the version that uses the maximin sampling criterion and the best-model strategy is a recommended choice. Moreover, the second-order ARBF-HDMR model significantly outperforms the first-order model; however, if the computational budget is strictly limited (e.g., 2n + 1 < Nmax ≪ 2n2 + 2), the first-order model becomes a better choice. Finally, it is noteworthy that the proposed modeling framework can work with other metamodeling techniques. |
| Starting Page | 1233 |
| Ending Page | 1250 |
| Page Count | 18 |
| File Format | PDF HTM / HTML |
| DOI | 10.1007/s00158-017-1807-0 |
| Alternate Webpage(s) | http://www.cil.ntu.edu.sg/Courses/papers/journal/ARBF-HDMR.pdf |
| Alternate Webpage(s) | https://doi.org/10.1007/s00158-017-1807-0 |
| Volume Number | 57 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
