Progressive transfer learning for advancing machine learning-based reduced-order modeling

Progressive transfer learning for advancing machine learning-based reduced-order modeling

Abstract To maximize knowledge transfer and improve the data requirement for data-driven machine learning (ML) modeling, a progressive transfer learning for reduced-order modeling (p-ROM) framework is proposed. A key concept of p-ROM is to selectively transfer knowledge from previously trained ML mo...

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Podrobná bibliografie
Hlavní autoři: Teeratorn Kadeethum, Daniel O’Malley, Youngsoo Choi, Hari S. Viswanathan, Hongkyu Yoon
Médium: Článek
Jazyk:English
Vydáno: Nature Portfolio 2024-07-01
Edice:Scientific Reports
On-line přístup:https://doi.org/10.1038/s41598-024-64778-y

Internet

https://doi.org/10.1038/s41598-024-64778-y

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