Long-time integration of partial differential equations based on a sliding-interval physics-informed neural network.

Huang W, Shao J, Yang M, Ruan Y, Fan X, Li H

DOI: 10.1103/9xdz-bd5f
Published: 2026 Aug
Container: Physical review. E
Publisher: Not recorded
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1103/9xdz-bd5f,
  title = {Long-time integration of partial differential equations based on a sliding-interval physics-informed neural network.},
  author = {Huang W and Shao J and Yang M and Ruan Y and Fan X and Li H},
  year = {2026},
  journal = {Physical review. E},
  doi = {10.1103/9xdz-bd5f},
  url = {https://doi.org/10.1103/9xdz-bd5f}
}

RIS

TY  - JOUR
TI  - Long-time integration of partial differential equations based on a sliding-interval physics-informed neural network.
AU  - Huang W
AU  - Shao J
AU  - Yang M
AU  - Ruan Y
AU  - Fan X
AU  - Li H
PY  - 2026
JO  - Physical review. E
DO  - 10.1103/9xdz-bd5f
UR  - https://doi.org/10.1103/9xdz-bd5f
ER  -

APA

W, H., J, S., M, Y., Y, R., X, F., & H, L. (2026). Long-time integration of partial differential equations based on a sliding-interval physics-informed neural network.. Physical review. E. https://doi.org/10.1103/9xdz-bd5f

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pubmed · retrieved 2026-09-24T22:58:09.831Z