The discrete empirical interpolation method in class identification and data summarization
EP Hendryx Lyons - Wiley Interdisciplinary Reviews …, 2024 - Wiley Online Library
The discrete empirical interpolation method (DEIM) is well established as a means of
performing model order reduction in approximating solutions to differential equations, but it …
performing model order reduction in approximating solutions to differential equations, but it …
[HTML][HTML] Enhancing solar radiation predictions through COA optimized neural networks and PCA dimensionality reduction
TKN Fariz, SS Basha - Energy Reports, 2024 - Elsevier
The inherent variability and uncertainty of solar radiation, influenced by factors such as
seasons, weather, and cloud cover, pose significant challenges in accurately forecasting …
seasons, weather, and cloud cover, pose significant challenges in accurately forecasting …
NINNs: Nudging induced neural networks
Nudging induced neural networks (NINNs) algorithms are introduced to control and improve
the accuracy of deep neural networks (DNNs). The NINNs framework can be applied to …
the accuracy of deep neural networks (DNNs). The NINNs framework can be applied to …