Výsledky vyhledávání - boundary element methods for initial value AND initial-boundary value problems involving pred~

A physics-inspired neural network to solve partial differential equations – application in diffusion-induced stress.

Autoři: Xue, Yuan Li, Yong Zhang, Kai a další

Zdroj: Physical Chemistry Chemical Physics (PCCP); 4/7/2022, Vol. 24 Issue 13, p7937-7949, 13p

Efficient integration of deep neural networks in sequential multiscale simulations.

Autoři: Tröger, Jendrik‐Alexander Eivazi, Hamidreza Hartmann, Stefan a další

Zdroj: PAMM: Proceedings in Applied Mathematics & Mechanics; Dec2023, Vol. 23 Issue 4, p1-8, 8p

Témata: ARTIFICIAL neural networks, AUTOMATIC differentiation, BOUNDARY value problems

A Gradient-Variance Weighting Physics-Informed Neural Network for Solving Integer and Fractional Partial Differential Equations.

Autoři: Zhang, Liang Liu, Quansheng Zhang, Ruigang a další

Zdroj: Applied Sciences (2076-3417); Oct2025, Vol. 15 Issue 20, p11137, 16p

Témata: PARTIAL differential equations, FRACTIONAL differential equations, COST functions, SCIENTIFIC computing, MACHINE learning, COMPUTER simulation

Well-posedness and numerical treatment of the Blackstock equation in nonlinear acoustics.

Autoři: Fritz, Marvin Nikolić, Vanja Wohlmuth, Barbara

Zdroj: Mathematical Models & Methods in Applied Sciences; Dec2018, Vol. 28 Issue 13, p2557-2597, 41p

Témata: NONLINEAR wave equations, DIRICHLET problem, BOUNDARY value problems, FIXED point theory, FINITE element method, NONLINEAR acoustics

An enhanced deep neural network with global adaptive weighted gradient for solving hyperbolic partial differential equations.

Autoři: Wu, Wei Zhao, Jiebin

Zdroj: European Physical Journal Plus; Jul2025, Vol. 140 Issue 7, p1-21, 21p

Multi-domain physics-informed neural networks for solving transient heat conduction problems in multilayer materials.

Autoři: Zhang, Benrong Wang, Fajie Qiu, Lin

Zdroj: Journal of Applied Physics; 6/28/2023, Vol. 133 Issue 24, p1-17, 17p

Témata: HEAT conduction, ARTIFICIAL neural networks, DEEP learning, TEMPERATURE distribution

A deep learning method for solving thermoelastic coupling problem.

Autoři: Fang, Ruoshi Zhang, Kai Song, Ke a další

Zdroj: Zeitschrift für Naturforschung Section A: A Journal of Physical Sciences; Aug2024, Vol. 79 Issue 8, p851-871, 21p

Témata: THERMAL stresses, THERMOELASTICITY, ENGINEERING, DEEP learning, EQUATIONS

From Spectrum to Image: A Novel Deep Clustering Network for Lactose-Free Milk Adulteration Detection.

Autoři: Zhang, Chong Ding, Shankui He, Ying

Zdroj: Information; Jun2025, Vol. 16 Issue 6, p498, 24p

Témata: NEAR infrared spectroscopy, AUTOENCODERS, FOOD safety, ADULTERATIONS, SILHOUETTES

A deep learning framework for predicting the spread of diffusion diseases.

Autoři: Chen, Xiao Li, Fuxiang Lian, Hairong a další

Zdroj: Electronic Research Archive; 2025, Vol. 33 Issue 4, p1-28, 28p

Témata: ARTIFICIAL neural networks, DEEP learning, INFECTIOUS disease transmission, INFORMATION networks, POPULATION dynamics

Physics-Informed Neural Networks in Grid-Connected Inverters: A Review.

Autoři: Mahdouri, Ekram Al Al-Abri, Said Yousef, Hassan a další

Zdroj: Energies (19961073); Oct2025, Vol. 18 Issue 20, p5441, 19p

Témata: PARAMETER estimation, ELECTRIC inverters, MACHINE learning, FAULT diagnosis, OPTIMIZATION algorithms, SYSTEM identification, ENERGY infrastructure

Flow-dynamics informed Kolmogorov–Arnold networks for simulating subsonic compressible flow around airfoils.

Autoři: Sun, Jianren Fei, Zhongyang Qin, Pan

Zdroj: AIP Advances; Nov2025, Vol. 15 Issue 11, p1-20, 20p

Témata: FLUID flow, SUBSONIC flow, DEEP learning, AEROFOILS, ARTIFICIAL neural networks, NONLINEAR regression, PREDICTION models

Physics-informed deep learning to quantify anomalies for real-time fault mitigation in 3D printing.

Autoři: Uhrich, Benjamin Pfeifer, Nils Schäfer, Martin a další

Zdroj: Applied Intelligence; Mar2024, Vol. 54 Issue 6, p4736-4755, 20p

Témata: ARTIFICIAL neural networks, DEEP learning, THREE-dimensional printing, SELECTIVE laser melting, HEAT transfer, THERMAL stresses

Integrating symbolic regression with physics-informed neural networks for simulating nonlinear wave dynamics in arterial blood flow.

Autoři: Changdar, Satyasaran Bhaumik, Bivas Sadhukhan, Nabanita a další

Zdroj: Physics of Fluids; Dec2024, Vol. 36 Issue 12, p1-18, 18p

Témata: ARTIFICIAL neural networks, MACHINE learning, NONLINEAR differential equations, NONLINEAR waves, PARTIAL differential equations, SYMBOLIC computation

Topanga: A kinetic ion plasma code for large-scale ionospheric simulations on magnetohydrodynamic timescales.

Autoři: Belyaev, Mikhail A. Larson, David J. Cohen, Bruce I. a další

Zdroj: Physics of Plasmas; Jan2024, Vol. 31 Issue 1, p1-22, 22p

Témata: DISPLACEMENT currents (Electric), ELECTROMAGNETIC wave absorption, NEUMANN boundary conditions, MAXWELL equations, OHM'S law, ELECTROMAGNETIC pulses, ELECTRON-ion collisions

Equivariant neural operators for gradient-consistent topology optimization.

Autoři: Erzmann, David Dittmer, Sören

Zdroj: Journal of Computational Design & Engineering; Jun2024, Vol. 11 Issue 3, p91-100, 10p

Témata: PARTIAL differential equations, TOPOLOGY, LINEAR systems

Solving the non-local Fokker–Planck equations by deep learning.

Autoři: Jiang, Senbao Li, Xiaofan

Zdroj: Chaos; Apr2023, Vol. 33 Issue 4, p1-14, 14p

Témata: FOKKER-Planck equation, DEEP learning

Benzotriazoium Bis(2-Ethylhexyl) Phosphate Ionic Liquid as a Catalyst and Multifunctional Lubricant Additive: Synthesis, Optimization, Characterization, and Tribological Evaluation.

Autoři: Adavodi, Roshanak Dini, Ghasem

Zdroj: Arabian Journal for Science & Engineering (Springer Science & Business Media B.V. ); Jun2024, Vol. 49 Issue 6, p7995-8010, 16p

Témata: LUBRICANT additives, IONIC liquids, RESPONSE surfaces (Statistics), STEEL strip, PHOSPHORIC acid, CATALYSTS, PHOSPHATES

Optimal Error Estimates for Chebyshev Approximations of Functions with Endpoint Singularities in Fractional Spaces.

Autoři: Xie, Ruiyi Wu, Boying Liu, Wenjie

Zdroj: Journal of Scientific Computing; Sep2023, Vol. 96 Issue 3, p1-29, 29p

Spatial analysis of environmental factors influencing dust sources in the east of Iran using a new activelearning approach.

Autoři: Yariyan, Peyman Amiri, Mahdis Saffariha, Maryam a další

Zdroj: Geocarto International; 2022, Vol. 37 Issue 26, p11929-11954, 26p

Témata: FACTOR analysis, DUST storms, WIND speed, DUST

Geografický termín: IRAN

Physics-informed neural networks (PINNs) for fluid mechanics: a review.

Autoři: Cai, Shengze Mao, Zhiping Wang, Zhicheng a další

Zdroj: Acta Mechanica Sinica; Dec2021, Vol. 37 Issue 12, p1727-1738, 12p