123 related articles for article (PubMed ID: 38526983)
1. The improved backward compatible physics-informed neural networks for reducing error accumulation and applications in data-driven higher-order rogue waves.
Lin S; Chen Y
Chaos; 2024 Mar; 34(3):. PubMed ID: 38526983
[TBL] [Abstract][Full Text] [Related]
2. Physics-informed neural networks based on adaptive weighted loss functions for Hamilton-Jacobi equations.
Liu Y; Cai L; Chen Y; Wang B
Math Biosci Eng; 2022 Sep; 19(12):12866-12896. PubMed ID: 36654026
[TBL] [Abstract][Full Text] [Related]
3. The line rogue wave solutions of the nonlocal Davey-Stewartson I equation with PT symmetry based on the improved physics-informed neural network.
Zhang Y; Liu H; Wang L; Sun W
Chaos; 2023 Jan; 33(1):013118. PubMed ID: 36725619
[TBL] [Abstract][Full Text] [Related]
4. PT-symmetric PINN for integrable nonlocal equations: Forward and inverse problems.
Peng WQ; Chen Y
Chaos; 2024 Apr; 34(4):. PubMed ID: 38579150
[TBL] [Abstract][Full Text] [Related]
5. Physics-informed neural networks to solve lumped kinetic model for chromatography process.
Tang SY; Yuan YH; Chen YC; Yao SJ; Wang Y; Lin DQ
J Chromatogr A; 2023 Oct; 1708():464346. PubMed ID: 37716084
[TBL] [Abstract][Full Text] [Related]
6. Physics Informed Neural Networks (PINN) for Low Snr Magnetic Resonance Electrical Properties Tomography (MREPT).
Inda AJG; Huang SY; İmamoğlu N; Qin R; Yang T; Chen T; Yuan Z; Yu W
Diagnostics (Basel); 2022 Oct; 12(11):. PubMed ID: 36359471
[TBL] [Abstract][Full Text] [Related]
7. A Novel Hybrid Deep Learning Method for Predicting the Flow Fields of Biomimetic Flapping Wings.
Hu F; Tay W; Zhou Y; Khoo B
Biomimetics (Basel); 2024 Jan; 9(2):. PubMed ID: 38392118
[TBL] [Abstract][Full Text] [Related]
8. Modified failproof physics-informed neural network framework for fast and accurate optical fiber transmission link modeling.
Uduagbomen J; Leeson MS; Liu Z; Lakshminarayana S; Xu T
Appl Opt; 2024 May; 63(14):3794-3802. PubMed ID: 38856342
[TBL] [Abstract][Full Text] [Related]
9. A Combination of Deep Neural Networks and Physics to Solve the Inverse Problem of Burger's Equation.
Alkhadhr S; Almekkawy M
Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov; 2021():4465-4468. PubMed ID: 34892210
[TBL] [Abstract][Full Text] [Related]
10. Quantifying local and global mass balance errors in physics-informed neural networks.
Mamud ML; Mudunuru MK; Karra S; Ahmmed B
Sci Rep; 2024 Jul; 14(1):15541. PubMed ID: 38969678
[TBL] [Abstract][Full Text] [Related]
11. Constructing Physics-Informed Neural Networks with Architecture Based on Analytical Modification of Numerical Methods by Solving the Problem of Modelling Processes in a Chemical Reactor.
Tarkhov D; Lazovskaya T; Malykhina G
Sensors (Basel); 2023 Jan; 23(2):. PubMed ID: 36679461
[TBL] [Abstract][Full Text] [Related]
12. Prediction of phase transition and time-varying dynamics of the (2+1)-dimensional Boussinesq equation by parameter-integrated physics-informed neural networks with phase domain decomposition.
Liu H; Wang L; Zhang Y; Lu G; Liu L
Phys Rev E; 2023 Oct; 108(4-2):045303. PubMed ID: 37978704
[TBL] [Abstract][Full Text] [Related]
13. Wave Equation Modeling via Physics-Informed Neural Networks: Models of Soft and Hard Constraints for Initial and Boundary Conditions.
Alkhadhr S; Almekkawy M
Sensors (Basel); 2023 Mar; 23(5):. PubMed ID: 36904994
[TBL] [Abstract][Full Text] [Related]
14. Physics-informed neural network with transfer learning (TL-PINN) based on domain similarity measure for prediction of nuclear reactor transients.
Prantikos K; Chatzidakis S; Tsoukalas LH; Heifetz A
Sci Rep; 2023 Oct; 13(1):16840. PubMed ID: 37803015
[TBL] [Abstract][Full Text] [Related]
15. Defect driven physics-informed neural network framework for fatigue life prediction of additively manufactured materials.
Wang L; Zhu SP; Luo C; Niu X; He JC
Philos Trans A Math Phys Eng Sci; 2023 Nov; 381(2260):20220386. PubMed ID: 37742712
[TBL] [Abstract][Full Text] [Related]
16. Physics-informed neural networks for hydraulic transient analysis in pipeline systems.
Ye J; Do NC; Zeng W; Lambert M
Water Res; 2022 Aug; 221():118828. PubMed ID: 35841787
[TBL] [Abstract][Full Text] [Related]
17. A High-Efficient Hybrid Physics-Informed Neural Networks Based on Convolutional Neural Network.
Fang Z
IEEE Trans Neural Netw Learn Syst; 2022 Oct; 33(10):5514-5526. PubMed ID: 33848251
[TBL] [Abstract][Full Text] [Related]
18. Gradient Statistics-Based Multi-Objective Optimization in Physics-Informed Neural Networks.
Vemuri SK; Denzler J
Sensors (Basel); 2023 Oct; 23(21):. PubMed ID: 37960365
[TBL] [Abstract][Full Text] [Related]
19. The Old and the New: Can Physics-Informed Deep-Learning Replace Traditional Linear Solvers?
Markidis S
Front Big Data; 2021; 4():669097. PubMed ID: 34870188
[TBL] [Abstract][Full Text] [Related]
20. FDM data driven U-Net as a 2D Laplace PINN solver.
Maria Antony AN; Narisetti N; Gladilin E
Sci Rep; 2023 Jun; 13(1):9116. PubMed ID: 37277366
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
