Physics-Informed Machine Learning for Uncertainty Reduction in Time Response Reconstruction of a Dynamic System
Author:
Affiliation:
1. Villanova University, Villanova, PA, USA
Funder
Office of Naval Research
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Networks and Communications
Link
http://xplorestaging.ieee.org/ielx7/4236/9841406/09764364.pdf?arnumber=9764364
Reference22 articles.
1. Physics-guided convolutional neural network (PhyCNN) for data-driven seismic response modeling
2. Physics-Guided Architecture (PGA) of Neural Networks for Quantifying Uncertainty in Lake Temperature Modeling
3. Discovery of Physics From Data: Universal Laws and Discrepancies
4. Learning Particle Physics by Example: Location-Aware Generative Adversarial Networks for Physics Synthesis
5. Fault identification and severity analysis of rolling element bearings using phase space topology;mohamad;J Vib Control,2020
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