@Article{EAJAM-14-3,
author = {Piao, Guang-Ri and Lee, Hyung-Chun},
title = {Real-Time Computing for a Parameterized Feedback Control Problem of Boussinesq Equations by POD and Deep Learning},
journal = {East Asian Journal on Applied Mathematics},
year = {2024},
volume = {14},
number = {3},
pages = {507--529},
abstract = {<p style="text-align: justify;">An efficient real-time computational method for a feedback control problem
of the Boussinesq equations is studied. We consider a simple and effective feedback control law based on the relationship between the control and adjoint variables in the optimality system. We investigate a closure type modeling in reduced order model (ROM) of
this problem for real-time computing. In order to improve the existing well-known POD-ROM method, the deep learning technique, which is currently being actively researched,
is studied and applied. Computational results presented show that the suggested methods work well.</p>},
issn = {2079-7370},
doi = {https://doi.org/10.4208/eajam.2023-094.250623},
url = {https://global-sci.com/article/91047/real-time-computing-for-a-parameterized-feedback-control-problem-of-boussinesq-equations-by-pod-and-deep-learning}
}