Editorial: Special issue on advanced optimization enabling digital twin technology
Author:
Publisher
Springer Science and Business Media LLC
Subject
Control and Optimization,Computer Graphics and Computer-Aided Design,Computer Science Applications,Control and Systems Engineering,Software
Link
https://link.springer.com/content/pdf/10.1007/s00158-023-03676-9.pdf
Reference21 articles.
1. Cao P, Zhang Y, Zhou K, Tang J (2023) A reinforcement learning hyper-heuristic in multi-objective optimization with application to structural damage identification. Struct Multidisc Optim 66(1):16. https://doi.org/10.1007/s00158-022-03432-5
2. Chen J, Meng C, Gao Y, Liu Y (2022) Multi-fidelity neural optimization machine for Digital Twins. Struct Multidisc Optim 65(12):340. https://doi.org/10.1007/s00158-022-03443-2
3. Fillmore TB, Wu Z, Vega MA, Hu Z, Todd MD (2022) A surrogate model to accelerate non-intrusive global–local simulations of cracked steel structures. Struct Multidisc Optim 65(7):208. https://doi.org/10.1007/s00158-022-03287-w
4. Geng R, Li M, Hu Z, Han Z, Zheng R (2022) Digital Twin in smart manufacturing: remote control and virtual machining using VR and AR technologies. Struct Multidisc Optim 65(11):321. https://doi.org/10.1007/s00158-022-03426-3
5. Haftka RT, Zhou M, Queipo NV (2019) Replication of results. Struct Multidisc Optim 60(2):405–409. https://doi.org/10.1007/s00158-019-02298-4
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