An active-learning probabilistic neural network for feasibility classification of constrained engineering optimization problems
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Science Applications,General Engineering,Modeling and Simulation,Software
Link
https://link.springer.com/content/pdf/10.1007/s00366-021-01441-4.pdf
Reference36 articles.
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3. Ruan X, Jiang P, Zhou Q, Hu J, Shu L (2020) Variable-fidelity probability of improvement method for efficient global optimization of expensive black-box problems. Struct Multidiscip Optim 62(6):3021–3052
4. Zhou Q, Wu J, Xue T, Jin P (2021) A two-stage adaptive multi-fidelity surrogate model-assisted multi-objective genetic algorithm for computationally expensive problems. Eng Comput 37:623–639
5. Zeng P, Li T, Chen Y, Jimenez R, Feng X, Senent S (2020) New collocation method for stochastic response surface reliability analyses. Eng Comput 36:1751–1762
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