2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Proceedings, pages 596-603
Multi-Objective Discovery of PDE Systems Using Evolutionary Approach
Publication type: Proceedings Article
Publication date: 2021-06-28
—
Abstract
Usually, the data-driven methods of the systems of partial differential equations (PDEs) discovery are limited to the scenarios, when the result can be manifested as the single vector equation form. However, this approach restricts the application to the real cases, where, for example, the form of the external forcing is of interest for the researcher and can not be described by the component of the vector equation. In the paper, a multi-objective co-evolution algorithm is proposed. The single equations within the system and the system itself are evolved simultaneously to obtain the system. This approach allows discovering the systems with the form-independent equations. In contrast to the single vector equation, a component-wise system is more suitable for expert interpretation and, therefore, for applications. The example of the two-dimensional Navier-Stokes equation is considered.
Citations by journals
|
1
|
|
|
Processes
|
Processes
1 publication, 25%
|
|
1
|
Citations by publishers
|
1
|
|
|
Multidisciplinary Digital Publishing Institute (MDPI)
|
Multidisciplinary Digital Publishing Institute (MDPI)
1 publication, 25%
|
|
IEEE
|
IEEE
1 publication, 25%
|
|
1
|
- We do not take into account publications that without a DOI.
- Statistics recalculated only for publications connected to researchers, organizations and labs registered on the platform.
- Statistics recalculated weekly.
{"yearsCitations":{"type":"bar","data":{"show":true,"labels":[2022,2023],"ids":[0,0],"codes":[0,0],"imageUrls":["",""],"datasets":[{"label":"Citations number","data":[1,3],"backgroundColor":["#3B82F6","#3B82F6"],"percentage":["25","75"],"barThickness":null}]},"options":{"indexAxis":"x","maintainAspectRatio":true,"scales":{"y":{"ticks":{"precision":0,"autoSkip":false,"font":{"family":"Montserrat"},"color":"#000000"}},"x":{"ticks":{"stepSize":1,"precision":0,"font":{"family":"Montserrat"},"color":"#000000"}}},"plugins":{"legend":{"position":"top","labels":{"font":{"family":"Montserrat"},"color":"#000000"}},"title":{"display":true,"text":"Citations per year","font":{"size":24,"family":"Montserrat","weight":600},"color":"#000000"}}}},"journals":{"type":"bar","data":{"show":true,"labels":["Processes"],"ids":[19796],"codes":[0],"imageUrls":["\/storage\/images\/resized\/MjH1ITP7lMYGxeqUZfkt2BnVLgjkk413jwBV97XX_medium.webp"],"datasets":[{"label":"","data":[1],"backgroundColor":["#3B82F6"],"percentage":[25],"barThickness":13}]},"options":{"indexAxis":"y","maintainAspectRatio":false,"scales":{"y":{"ticks":{"precision":0,"autoSkip":false,"font":{"family":"Montserrat"},"color":"#000000"}},"x":{"ticks":{"stepSize":null,"precision":0,"font":{"family":"Montserrat"},"color":"#000000"}}},"plugins":{"legend":{"position":"top","labels":{"font":{"family":"Montserrat"},"color":"#000000"}},"title":{"display":true,"text":"Journals","font":{"size":24,"family":"Montserrat","weight":600},"color":"#000000"}}}},"publishers":{"type":"bar","data":{"show":true,"labels":["Multidisciplinary Digital Publishing Institute (MDPI)","IEEE"],"ids":[202,6953],"codes":[0,0],"imageUrls":["\/storage\/images\/resized\/MjH1ITP7lMYGxeqUZfkt2BnVLgjkk413jwBV97XX_medium.webp","\/storage\/images\/resized\/6scCJegesojp2jubwY3uKCzTAmgsaH2GIFlg6Hfk_medium.webp"],"datasets":[{"label":"","data":[1,1],"backgroundColor":["#3B82F6","#3B82F6"],"percentage":[25,25],"barThickness":13}]},"options":{"indexAxis":"y","maintainAspectRatio":false,"scales":{"y":{"ticks":{"precision":0,"autoSkip":false,"font":{"family":"Montserrat"},"color":"#000000"}},"x":{"ticks":{"stepSize":null,"precision":0,"font":{"family":"Montserrat"},"color":"#000000"}}},"plugins":{"legend":{"position":"top","labels":{"font":{"family":"Montserrat"},"color":"#000000"}},"title":{"display":true,"text":"Publishers","font":{"size":24,"family":"Montserrat","weight":600},"color":"#000000"}}}}}
Metrics
Cite this
GOST |
RIS |
BibTex
Cite this
GOST
Copy
Maslyaev M., Hvatov A. Multi-Objective Discovery of PDE Systems Using Evolutionary Approach // 2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Proceedings. 2021. pp. 596-603.
GOST all authors (up to 50)
Copy
Maslyaev M., Hvatov A. Multi-Objective Discovery of PDE Systems Using Evolutionary Approach // 2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Proceedings. 2021. pp. 596-603.
Cite this
RIS
Copy
TY - CPAPER
DO - 10.1109/CEC45853.2021.9504712
UR - https://doi.org/10.1109%2FCEC45853.2021.9504712
TI - Multi-Objective Discovery of PDE Systems Using Evolutionary Approach
T2 - 2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Proceedings
AU - Maslyaev, Mikhail
AU - Hvatov, Alexander
PY - 2021
DA - 2021/06/28 00:00:00
SP - 596-603
ER -
Cite this
BibTex
Copy
@inproceedings{2021_Maslyaev,
author = {Mikhail Maslyaev and Alexander Hvatov},
title = {Multi-Objective Discovery of PDE Systems Using Evolutionary Approach},
year = {2021},
pages = {596--603},
month = {jun}
}
Profiles