Identification of partial differential equations from noisy data with integrated knowledge discovery and embedding using evolutionary neural networks-Reference-Cited by-同舟云学术

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Identification of partial differential equations from noisy data with integrated knowledge discovery and embedding using evolutionary neural networks

Published:2024-03 Issue:2 Volume:14 Page:100511
ISSN:2095-0349
Container-title:Theoretical and Applied Mechanics Letters
language:en
Short-container-title:Theoretical and Applied Mechanics Letters

Author:

Zhou Hanyu^ORCID,Li Haochen^ORCID,Zhao Yaomin^ORCID

Funder

NSFC

Publisher

Elsevier BV

Reference25 articles.

1. Beyond the Data Deluge;Bell;Science,2009

2. Discovering governing equations from data by sparse identification of nonlinear dynamical systems;Brunton;Proc. Natl. Acad. Sci. U.S.A.,2016

3. Data-driven discovery of partial differential equations;Rudy;Sci. Adv.,2017

4. Data-driven and physical-based identification of partial differential equations for multivariable system;Cao;Theor. App. Mech. Lett.,2022

5. PDE-net: Learning PDEs from data;Long,2018

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