Achchab, Boujamaa
Unknown Affiliation

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

Two-dimensional Klein-Gordon and Sine-Gordon numerical solutions based on deep neural network Nouna, Soumaya; Nouna, Assia; Mansouri, Mohamed; Tammouch, Ilyas; Achchab, Boujamaa
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i2.pp1548-1560

Abstract

Due to the well-known dimensionality curse, developing effective numerical techniques to resolve partial differential equations proved a complex problem. We propose a deep learning technique for solving these problems. Feedforward neural networks (FNNs) use to approximate a partial differential equation with more robust and weaker boundaries and initial conditions. The framework called PyDEns could handle calculation fields that are not regular. Numerical exper- iments on two-dimensional Sine-Gordon and Klein-Gordon systems show the provided frameworks to be sufficiently accurate.