Zobrazeno 1 - 10
of 1 502
pro vyhledávání: '"S. L. Brunton"'
Publikováno v:
Royal Society Open Science, Vol 11, Iss 10 (2024)
Reduced-order models (ROMs) have been widely adopted in fluid mechanics, particularly in the context of Newtonian fluid flows. These models offer the ability to predict complex dynamics, such as instabilities and oscillations, at a considerably reduc
Externí odkaz:
https://doaj.org/article/bfd157fdb0e74bd18631b51bd6053d38
Publikováno v:
Machine Learning: Science and Technology, Vol 4, Iss 2, p 025012 (2023)
Machine learning has rapidly been adopted in virtually all areas of engineering in recent years. This paper develops a machine learning model capable of predicting the performance of parametrically generated enhanced microsurface geometries for cooli
Externí odkaz:
https://doaj.org/article/2cd7f7b9fcbd4daab6a3152028804c47
Publikováno v:
New Journal of Physics, Vol 23, Iss 3, p 033035 (2021)
Data-driven methods for establishing quantum optimal control (QOC) using time-dependent control pulses tailored to specific quantum dynamical systems and desired control objectives are critical for many emerging quantum technologies. We develop a dat
Externí odkaz:
https://doaj.org/article/84ae3ba6ed774465ac7a0e92da1dfdb1
Publikováno v:
International Marine Energy Journal, Vol 1, Iss 2 (Nov) (2018)
Cross-flow turbines have a number of potential advantages for hydrokinetic energy applications. Two novel control schemes for improving cross-flow turbine energy conversion are introduced and demonstrated through scale experiments. The first aims to
Externí odkaz:
https://doaj.org/article/b98c8c9787ec45988e1fb3f13f60b916
Publikováno v:
Complexity, Vol 2018 (2018)
We consider the application of Koopman theory to nonlinear partial differential equations and data-driven spatio-temporal systems. We demonstrate that the observables chosen for constructing the Koopman operator are critical for enabling an accurate
Externí odkaz:
https://doaj.org/article/52651b8f7eee47a4b81d1e85616576a1
Autor:
Wu, Yushan1 (AUTHOR), Qiao, Shi1 (AUTHOR), Zhong, Jitao1 (AUTHOR), Zhang, Lu1 (AUTHOR), Wang, Juan2 (AUTHOR), Hu, Bin1 (AUTHOR), Peng, Hong1,3 (AUTHOR) pengh@lzu.edu.cn
Publikováno v:
CNS Neuroscience & Therapeutics. Nov2024, Vol. 30 Issue 11, p1-14. 14p.
Publikováno v:
Foundations of Computational Mathematics. Oct2024, Vol. 24 Issue 5, p1595-1641. 47p.
Autor:
Mowlavi, Saviz1 (AUTHOR) mowlavi@merl.com, Benosman, Mouhacine1 (AUTHOR) benosman@merl.com
Publikováno v:
Scientific Reports. 9/28/2024, Vol. 14 Issue 1, p1-13. 13p.
Autor:
YUMENG WANG1 yw2bc@umsystem.edu, SHIPING ZHOU1 szb5g@umsystem.edu, YANZHI ZHANG1 zhangyanz@umsystem.edu
Publikováno v:
International Journal of Numerical Analysis & Modeling. 2024, Vol. 21 Issue 5, p716-738. 23p.
Autor:
Lanzoni, Daniele1, Rovaris, Fabrizio1, Martín-Encinar, Luis2, Fantasia, Andrea1, Bergamaschini, Roberto1 roberto.bergamaschini@unimib.it, Montalenti, Francesco1
Publikováno v:
APL Machine Learning. Sep2024, Vol. 2 Issue 3, p1-10. 10p.