Convergence analysis of neural networks for solving a free boundary problem

Xinyue Evelyn Zhao, Wenrui Hao, Bei Hu

Research output: Contribution to journalArticlepeer-review

Abstract

Free boundary problems deal with systems of partial differential equations, where the domain boundaries are apriori unknown. Due to this special characteristic, it is challenging to solve free boundary problems either theoretically or numerically. In this paper, we develop a novel approach for solving a modified Hele–Shaw problem based on the neural network discretization. The existence of the numerical solution with this discretization is established theoretically. We also numerically verify this approach by computing the symmetry-breaking solutions which are guided by the bifurcation analysis near the radially-symmetric branch. Moreover, we further verify the capability of this approach by computing some non-radially symmetric solutions which are not characterized by any theorems.

Original languageEnglish (US)
Pages (from-to)144-155
Number of pages12
JournalComputers and Mathematics with Applications
Volume93
DOIs
StatePublished - Jul 1 2021

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • Computational Theory and Mathematics
  • Computational Mathematics

Fingerprint

Dive into the research topics of 'Convergence analysis of neural networks for solving a free boundary problem'. Together they form a unique fingerprint.

Cite this