Results 51 to 60 of about 225,423 (289)
Noise-aware physics-informed machine learning for robust PDE discovery
Machine Learning: Science and Technology, 2023 This work is concerned with discovering the governing partial differential equation (PDE) of a physical system. Existing methods have demonstrated the PDE identification from finite observations but failed to maintain satisfying results against noisy ...
Pongpisit Thanasutives +3 more
doaj +1 more source
Intermaths, 2021 Um dos problemas encontrados na área de Engenharia Elétrica é o problema de despacho econômico (PDE), que visa reduzir o custo total da energia calculando a geração de cada unidade vinculada à rede.
João Vitor Dias +2 more
doaj +1 more source
AI in chemical engineering: From promise to practice
AIChE Journal, EarlyView.Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew +4 more
wiley +1 more source
Measuring cAMP Specific Phosphodiesterase Activity: A Two-step Radioassay
Bio-Protocol, 2020 Cyclic nucleotide degrading phosphodiesterase (PDE) enzymes are crucial to the fine tuning of cAMP signaling responses, playing a pivotal role in regulating the temporal and spatial characteristics of discrete cAMP nanodomains and hence the activity of ...
Connor Blair +2 more
doaj +1 more source
Sensors, 2022 This work proposes a unifying framework for extending PDE-constrained Large Deformation Diffeomorphic Metric Mapping (PDE-LDDMM) with the sum of squared differences (SSD) to PDE-LDDMM with different image similarity metrics.
Monica Hernandez +2 more
doaj +1 more source
, 2008 We apply a version of the dressing method to a system of four dimensional nonlinear Partial Differential Equations (PDEs), which contains both Pohlmeyer equation (i.e.
Bogdanov L V +13 more
core +2 more sources
Advanced Intelligent Discovery, EarlyView.This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee +3 more
wiley +1 more source
Single freeform surface design for prescribed input wavefront and target irradiance
, 2017 In beam shaping applications, the minimization of the number of necessary optical elements for the beam shaping process can benefit the compactness of the optical system and reduce its cost.
Bösel, Christoph, Gross, Herbert
core +1 more source
PDE-Net: Learning PDEs from Data
, 2017 In this paper, we present an initial attempt to learn evolution PDEs from data. Inspired by the latest development of neural network designs in deep learning, we propose a new feed-forward deep network, called PDE-Net, to fulfill two objectives at the same time: to accurately predict dynamics of complex systems and to uncover the underlying hidden PDE ...
Long, Zichao +3 more
openaire +2 more sources
ACM Transactions on Modeling and Computer Simulation, 2019 In this article, we present experiences implementing a general Parallel Discrete Event Simulation (PDES) accelerator on a Field Programmable Gate Array (FPGA). The accelerator can be specialized to any particular simulation model by defining the object states and the event handling code, which are then synthesized into a custom accelerator for the ...
Shafiur Rahman +2 more
openaire +1 more source