Kolmogorov–Arnold Networks for Reduced-Order Modeling in Unsteady Aerodynamics and Aeroelasticity

Kolmogorov–Arnold Networks for Reduced-Order Modeling in Unsteady Aerodynamics and Aeroelasticity

Kolmogorov–Arnold Networks (KANs) are a recent development in machine learning, offering strong functional representation capabilities, enhanced interpretability, and reduced parameter complexity. Leveraging these advantages, this paper proposes a KAN-based reduced-order model (ROM) for unsteady aer...

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Bibliographic Details
Main Authors: Yuchen Zhang, Han Tang, Lianyi Wei, Guannan Zheng, Guowei Yang
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Applied Sciences
Subjects:
Kolmogorov–Arnold Networks
reduced-order model
unsteady aerodynamics
nonlinear aeroelasticity
Online Access:https://www.mdpi.com/2076-3417/15/11/5820
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