Physics-informed neural networks with Riccati-type pseudopotential constraints for solving nonlinear evolution equations

Junchao Wan, Hui Wang, Yunhu Wang

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DOI: 10.1063/5.0348469
Published: 2026-09-01
Container: Chaos: An Interdisciplinary Journal of Nonlinear Science
Publisher: AIP Publishing
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1063/5.0348469,
  title = {Physics-informed neural networks with Riccati-type pseudopotential constraints for solving nonlinear evolution equations},
  author = {Junchao Wan and Hui Wang and Yunhu Wang},
  year = {2026},
  journal = {Chaos: An Interdisciplinary Journal of Nonlinear Science},
  doi = {10.1063/5.0348469},
  url = {https://doi.org/10.1063/5.0348469}
}

RIS

TY  - JOUR
TI  - Physics-informed neural networks with Riccati-type pseudopotential constraints for solving nonlinear evolution equations
AU  - Junchao Wan
AU  - Hui Wang
AU  - Yunhu Wang
PY  - 2026
JO  - Chaos: An Interdisciplinary Journal of Nonlinear Science
DO  - 10.1063/5.0348469
UR  - https://doi.org/10.1063/5.0348469
ER  -

APA

Wan, J., Wang, H., & Wang, Y. (2026). Physics-informed neural networks with Riccati-type pseudopotential constraints for solving nonlinear evolution equations. Chaos: An Interdisciplinary Journal of Nonlinear Science. https://doi.org/10.1063/5.0348469

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crossref · retrieved 2026-11-08T08:38:36.709Z