Hybrid physics-informed artificial intelligence for high-fidelity modeling and optimization of electrical systems.

Nyangon J

DOI: 10.3389/frai.2026.1751785
Published: 2026
Container: Frontiers in artificial intelligence
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3389/frai.2026.1751785,
  title = {Hybrid physics-informed artificial intelligence for high-fidelity modeling and optimization of electrical systems.},
  author = {Nyangon J},
  year = {2026},
  journal = {Frontiers in artificial intelligence},
  doi = {10.3389/frai.2026.1751785},
  url = {https://doi.org/10.3389/frai.2026.1751785}
}

RIS

TY  - JOUR
TI  - Hybrid physics-informed artificial intelligence for high-fidelity modeling and optimization of electrical systems.
AU  - Nyangon J
PY  - 2026
JO  - Frontiers in artificial intelligence
DO  - 10.3389/frai.2026.1751785
UR  - https://doi.org/10.3389/frai.2026.1751785
ER  -

APA

J, N. (2026). Hybrid physics-informed artificial intelligence for high-fidelity modeling and optimization of electrical systems.. Frontiers in artificial intelligence. https://doi.org/10.3389/frai.2026.1751785

Source records

pubmed · retrieved 2026-09-25T17:08:10.117Z