Slow Invariant Manifolds of Singularly Perturbed Systems via Physics-Informed Machine Learning-Reference-Cited by-同舟云学术

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Slow Invariant Manifolds of Singularly Perturbed Systems via Physics-Informed Machine Learning

Published:2024-07-05 Issue:4 Volume:46 Page:C297-C322
ISSN:1064-8275
Container-title:SIAM Journal on Scientific Computing
language:en
Short-container-title:SIAM J. Sci. Comput.

Author:

Patsatzis Dimitrios¹^ORCID,Fabiani Gianluca¹^ORCID,Russo Lucia²^ORCID,Siettos Constantinos³^ORCID

Affiliation:

1. Modelling Engineering Risk and Complexity, Scuola Superiore Meridionale, Naples 80138 Italy.

2. Institute of Science and Technology for Energy and Sustainable Mobility (STEMS), Consiglio Nazionale delle Ricerche, Naples 80125 Italy.

3. Dipartimento di Matematica e Applicazioni “Renato Caccioppoli”, Università degli Studi di Napoli Federico II, Naples 80126 Italy.

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Reference90 articles.

1. Modelling of nonlinear process dynamics using Kohonen's neural networks, fuzzy systems and Chebyshev series

2. The Isomap Algorithm and Topological Stability

3. Universal approximation bounds for superpositions of a sigmoidal function

4. ATTRACTOR MODELING AND EMPIRICAL NONLINEAR MODEL REDUCTION OF DISSIPATIVE DYNAMICAL SYSTEMS

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Nonlinear discrete-time observers with Physics-Informed Neural Networks;Chaos, Solitons & Fractals;2024-09

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