Physics-based loss and machine learning approach in application to non-Newtonian fluids flow modeling-Reference-Cited by-同舟云学术

Physics-based loss and machine learning approach in application to non-Newtonian fluids flow modeling

Published:2022-07-18 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Congress on Evolutionary Computation (CEC)
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Author:

Kornaeva Elena¹,Kornaev Alexey²,Fetisov Alexander³,Stebakov Ivan³,Ibragimov Bulat⁴

Affiliation:

1. Orel State University,Dept. of Information Systems and Digital Technologies,Orel,Russia

2. Research Center for Artificial Intelligence, Innopolis University,Innopolis,Russia

3. Orel State University,Dept. of Mechatronics, Mechanics, and Robotics,Orel,Russia

4. University of Copenhagen,Dept. of Computer Science,Copenhagen,Denmark

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9870216/9870201/09870411.pdf?arnumber=9870411

Reference27 articles.

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4. Neural-network-based approximations for solving partial differential equations

5. An energy approach to the solution of partial differential equations in computational mechanics via machine learning: Concepts, implementation and applications;samaniego;Computer Methods in Applied Mechanics and Engineering,2019

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