106 related articles for article (PubMed ID: 38949289)
1. Physics-informed neural network for acoustic resonance analysis in a one-dimensional acoustic tube.
Yokota K; Kurahashi T; Abe M
J Acoust Soc Am; 2024 Jul; 156(1):30-43. PubMed ID: 38949289
[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. 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]
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. 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]
6. Strategies for multi-case physics-informed neural networks for tube flows: a study using 2D flow scenarios.
Wong HS; Chan WX; Li BH; Yap CH
Sci Rep; 2024 May; 14(1):11577. PubMed ID: 38773243
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. 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]
9. 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]
10. 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]
11. 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]
12. Physics-informed neural network for fast prediction of temperature distributions in cancerous breasts as a potential efficient portable AI-based diagnostic tool.
Mukhmetov O; Zhao Y; Mashekova A; Zarikas V; Ng EYK; Aidossov N
Comput Methods Programs Biomed; 2023 Dec; 242():107834. PubMed ID: 37852143
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. 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]
15. Spatial domain decomposition-based physics-informed neural networks for practical acoustic propagation estimation under ocean dynamics.
Duan J; Zhao H; Song J
J Acoust Soc Am; 2024 May; 155(5):3306-3321. PubMed ID: 38752840
[TBL] [Abstract][Full Text] [Related]
16. On acoustic fields of complex scatters based on physics-informed neural networks.
Wang H; Li J; Wang L; Liang L; Zeng Z; Liu Y
Ultrasonics; 2023 Feb; 128():106872. PubMed ID: 36323059
[TBL] [Abstract][Full Text] [Related]
17. Predicting the Early-Age Time-Dependent Behaviors of a Prestressed Concrete Beam by Using Physics-Informed Neural Network.
Park HW; Hwang JH
Sensors (Basel); 2023 Jul; 23(14):. PubMed ID: 37514943
[TBL] [Abstract][Full Text] [Related]
18. SWENet: A Physics-Informed Deep Neural Network (PINN) for Shear Wave Elastography.
Yin Z; Li GY; Zhang Z; Zheng Y; Cao Y
IEEE Trans Med Imaging; 2024 Apr; 43(4):1434-1448. PubMed ID: 38032772
[TBL] [Abstract][Full Text] [Related]
19. 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]
20. 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]
[Next] [New Search]