Solving second-order nonlinear evolution partial differential equations using deep learning*

Jun Li(李军),Yong Chen(陈勇)

Communications in Theoretical Physics ›› 2020, Vol. 72 ›› Issue (10) : 105005.

PDF(2003 KB)
Welcome to visit Communications in Theoretical Physics,
PDF(2003 KB)
Communications in Theoretical Physics ›› 2020, Vol. 72 ›› Issue (10) : 105005. DOI: 10.1088/1572-9494/aba243  CSTR: 32041.14.CTP.1572-9494/aba243
Mathematical Physics

Solving second-order nonlinear evolution partial differential equations using deep learning*

    {{javascript:window.custom_author_en_index=0;}}
  • {{article.zuoZhe_EN}}
Author information +
History +

HeighLight

{{article.keyPoints_en}}

Abstract

{{article.zhaiyao_en}}

Key words

QR code of this article

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations
{{article.zuoZheEn_L}}. {{article.title_en}}[J]. {{journal.qiKanMingCheng_EN}}, 2020, 72(10): 105005 https://doi.org/10.1088/1572-9494/aba243

References

List( Publishing order | Descend order by publishing year | Descend order by cited within ) Chart analysis

References

{{article.reference}}

Funding

RIGHTS & PERMISSIONS

{{article.copyrightStatement_en}}
{{article.copyrightLicense_en}}
PDF(2003 KB)

Accesses

Citation

Detail
Sections
Recommended
Copyright © Editorial Office of Communications in Theoretical Physics
Address: Institute of Theoretical Physics, Chinese Academy of Sciences,
Beijing 100190, China　
E-mail：ctp@itp.ac.cn
Website: https://ctp.itp.ac.cn　https://iopscience.org/ctp
Powered by Beijing Magtech Co., Ltd.

/

〈 〉