Application of sparse identification of nonlinear dynamics for physics-informed learning

Advances in machine learning and deep neural networks have enabled complex engineering tasks like image recognition, anomaly detection, regression, and multi-objective optimization, to name but a few. The complexity of the algorithm architecture, e.g., the number of hidden layers in a deep neural ne...

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Bibliographic Details

Published in:	2020 IEEE Aerospace Conference pp. 1 - 8
Main Author:	Corbetta, Matteo
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.03.2020
Subjects:	Aerodynamics Bayes methods Heuristic algorithms Libraries Machine learning Machine learning algorithms Mathematical models Nonlinear dynamical systems System dynamics Trajectory
Online Access:	Get full text
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