On the Neural Network Solution of One-Dimensional Wave Problem

Aditya Firman Ihsan

doi:10.29207/resti.v5i6.3565

Aditya Firman Ihsan Telkom University

DOI: https://doi.org/10.29207/resti.v5i6.3565

Keywords: Physics Informed Neural Network, wave problem, deep learning

Abstract

Artificial neural network has become an emerging popular method to handle various problems, especially in case where it has deep multiple neural layers. In this study, we use a deep artificial neural network model to solve one-dimensional wave equation, without any external datasets. Different type of boundary conditions, i.e., Dirichlet, Neumann, and Robin, are used. We analyze the model learning capabilities in a set of settings, such as data setup and the model width and depth. We also present some discussions of advantages and disadvantages of the model in comparison with other matured existing techniques to solve wave equation.

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