Results 91 to 100 of about 8,116 (238)
, 2005 Hürriyet Gazetesi Financial Times'da yayınlanmış İngram Pinn çizimli bir karikatürü ...
Pinn, İngram
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PSO-PINN: Physics-Informed Neural Networks Trained with Particle Swarm Optimization [PDF]
, 2022 Physics-informed neural networks (PINN) have recently emerged as a promising application of deep learning in a wide range of engineering and scientific problems based on partial differential equation (PDE) models.
Braga-Neto, Ulisses, Davi, Caio
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Applied SciencesPhysics-Informed Neural Networks (PINNs) provide a promising framework for solving partial differential equations (PDEs). By incorporating temporal causality, Causal PINN improves training stability in time-dependent problems.
Jinyu Hu, Jun-Jie Huang
doaj +1 more source
ÄSTHETIK DES JIDDISCHEN IN DER KLASSISCHEN MODERNE
German Life and Letters, EarlyView.ABSTRACT Der Beitrag erzählt die Geschichte der Entdeckung und Aufwertung des Jiddischen unter deutschsprachigen Schriftstellerinnen und Schriftstellern. Hatte die zunächst als Judendeutsch, Mauscheln oder Jargon bezeichnete Sprache in literarischen Texten des 19. Jahrhunderts vornehmlich eine mimetische Funktion, in der Regel wie bei Gustav Freytag in
Alexander Nebrig
wiley +1 more source
, 2017 This record was harvested from a previous catalogue system and will be withdrawn in 2025. Information in this record may be superseded or incomplete.
Australian Red Cross Society, National Office
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Geometric optimization of two-stage stamping dies for ultra-thin titanium bipolar plates using Sequential Physics-Informed Neural Networks [PDF]
Computer Methods in Materials ScienceBipolar plates are critical core components in proton exchange membrane fuel cells (PEMFCs). Titanium-based materials are highly favored due to their excellent corrosion resistance and high specific strength.
Zijie Ke +5 more
doaj +1 more source
Reduced order modelling of air‐puff test for corneal material characterisation
Journal of Microscopy, EarlyView.Abstract Models of the fluid–structure interaction (FSI) model for the air‐puff test were analysed. Using Abaqus, the air‐puff test is applied to eyes with varying biomechanical parameters, such as material properties, corneal thickness, and radius.
Osama M. Maklad, Muting Hao
wiley +1 more source
Comparison of Trefftz-Based PINNs and Standard PINNs Focusing on Structure Preservation
CoRRIn this study, we investigate the capability of physics-informed neural networks (PINNs) to preserve global physical structures by comparing standard PINNs with a Trefftz-based PINN (Trefftz-PINN). The target problem is the reproduction of mag-netic field-line structures in a helical fusion reactor configuration.
openaire +2 more sources
PINN Balls: Scaling Second-Order Methods for PINNs with Domain Decomposition and Adaptive Sampling
CoRRRecent advances in Scientific Machine Learning have shown that second-order methods can enhance the training of Physics-Informed Neural Networks (PINNs), making them a suitable alternative to traditional numerical methods for Partial Differential Equations (PDEs).
Andrea Bonfanti +5 more
openaire +2 more sources
Hyperspectral tomographic diffractive microscopy: Development and applications
Journal of Microscopy, EarlyView.Abstract Tomographic Diffractive Microscopy (TDM) provides label‐free three‐dimensional imaging of transparent samples with resolution surpassing confocal limits. At IRIMAS, successive instrumental developments since 2009 have enhanced TDM capabilities through transmission, reflection, isotropic, polarisation‐sensitive, and dual‐view configurations ...
Leonardo Pestana Legori +4 more
wiley +1 more source