ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2405.06443
  4. Cited By
Residual-based Attention Physics-informed Neural Networks for Efficient
  Spatio-Temporal Lifetime Assessment of Transformers Operated in Renewable
  Power Plants

Residual-based Attention Physics-informed Neural Networks for Efficient Spatio-Temporal Lifetime Assessment of Transformers Operated in Renewable Power Plants

10 May 2024
Ibai Ramirez
Joel Pino
David Pardo
Mikel Sanz
Luis Del Rio
Álvaro Ortiz
Kateryna Morozovska
J. Aizpurua
ArXiv (abs)PDFHTML

Papers citing "Residual-based Attention Physics-informed Neural Networks for Efficient Spatio-Temporal Lifetime Assessment of Transformers Operated in Renewable Power Plants"

2 / 2 papers shown
Title
Deep physical neural networks enabled by a backpropagation algorithm for
  arbitrary physical systems
Deep physical neural networks enabled by a backpropagation algorithm for arbitrary physical systems
Logan G. Wright
Tatsuhiro Onodera
Martin M. Stein
Tianyu Wang
Darren T. Schachter
Zoey Hu
Peter L. McMahon
PINNAI4CE
89
495
0
27 Apr 2021
Learning Unknown Physics of non-Newtonian Fluids
Learning Unknown Physics of non-Newtonian Fluids
B. Reyes
Amanda A. Howard
P. Perdikaris
A. Tartakovsky
PINN
52
48
0
26 Aug 2020
1