Spremljaj
Renato G. Nascimento
Renato G. Nascimento
AI Applied Scientist
Preverjeni e-poštni naslov na intel.com
Naslov
Navedeno
Navedeno
Leto
Hybrid physics-informed neural networks for lithium-ion battery modeling and prognosis
RG Nascimento, M Corbetta, CS Kulkarni, FAC Viana
Journal of Power Sources 513, 230526, 2021
1422021
A tutorial on solving ordinary differential equations using Python and hybrid physics-informed neural network
RG Nascimento, K Fricke, FAC Viana
Engineering Applications of Artificial Intelligence 96, 103996, 2020
1262020
Estimating model inadequacy in ordinary differential equations with physics-informed neural networks
FAC Viana, RG Nascimento, A Dourado, YA Yucesan
Computers & Structures 245, 106458, 2021
802021
Fleet prognosis with physics-informed recurrent neural networks
RG Nascimento, FAC Viana
arXiv preprint arXiv:1901.05512, 2019
752019
Cumulative damage modeling with recurrent neural networks
RG Nascimento, FAC Viana
AIAA Journal 58 (12), 5459-5471, 2020
462020
A framework for Li-ion battery prognosis based on hybrid Bayesian physics-informed neural networks
RG Nascimento, FAC Viana, M Corbetta, CS Kulkarni
Scientific Reports 13 (1), 13856, 2023
182023
Satellite image classification and segmentation with transfer learning
R Giorgiani do Nascimento, F Viana
Aiaa scitech 2020 forum, 1864, 2020
172020
Physics-informed neural networks package
FAC Viana, RG Nascimento, Y Yucesan, A Dourado
Zenodo. Retrieved from, 2019
142019
Quadcopter control optimization through machine learning
R Giorgiani do Nascimento, K Fricke, F Viana
AIAA Scitech 2020 Forum, 1148, 2020
122020
Quadcopter soft vertical landing control with hybrid physics-informed machine learning
K Fricke, R Giorgiani do Nascimento, F Viana
AIAA Scitech 2021 Forum, 1018, 2021
102021
Integrated development environment for analytic authoring
AK Subramaniyan, A Iankoulski, RG Do Nascimento
US Patent 10,296,296, 2019
92019
Li-ion battery aging with hybrid physics-informed neural networks and fleet-wide data
RG Nascimento, M Corbetta, CS Kulkarni, FAC Viana
Annual conference of the PHM society 13 (1), 2021
72021
Usage-based lifing of lithium-ion battery with hybrid physics-informed neural networks
R Giorgiani do Nascimento, F Viana, M Corbetta, CS Kulkarni
AIAA aviation 2021 forum, 3046, 2021
72021
System architecture for secure and rapid development, deployment and management of analytics and software systems
AK Subramaniyan, J Lazos, NC KUMAR, A Iankoulski, ...
US Patent 10,481,874, 2019
72019
Prognosis of li-ion batteries under large load variations using hybrid physics-informed neural networks
K Fricke, R Nascimento, M Corbetta, C Kulkarni, F Viana
Annual conference of the PHM society 15 (1), 2023
62023
Self-aware and self-registering software and analytics platform components
AK Subramaniyan, A Iankoulski, RG Do Nascimento
US Patent 10,459,774, 2019
62019
An accelerated life testing dataset for lithium-ion batteries with constant and variable loading conditions
K Fricke, R Nascimento, M Corbetta, C Kulkarni, F Viana
International Journal of Prognostics and Health Management 14 (2), 2023
32023
Quantifying uncertainty in Li-ion battery aging due to unknown usage with hybrid physics-informed neural networks
R Giorgiani do Nascimento, F Viana, M Corbetta, CS Kulkarni
AIAA scitech 2023 forum, 0536, 2023
32023
Lithium-ion battery prognosis with variational hybrid physics-informed neural networks
RG Nascimento
University of Central Florida, 2022
32022
Systems and methods for optimizing graphics processing for rapid large data visualization
AK Subramaniyan, AN Iankoulski, RG do Nascimento
US Patent 9,978,114, 2018
32018
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Članki 1–20