CAN ARTIFICIAL INTELLIGENCE PREDICT A TSUNAMI?

Daria Wójcik; Alicja Niewiadomska; Maciej Paszynski

doi:10.7494/csci.2025.26.4.7773

Authors

Daria Wójcik AGH University of Krakow https://orcid.org/0000-0002-6686-3795
Alicja Niewiadomska AGH University of Krakow
Maciej Paszynski AGH University of Krakow

DOI:

https://doi.org/10.7494/csci.2025.26.4.7773

Abstract

n this article, we build a model for tsunami simulation based on physics-informed neural networks and the finite difference method. We then check how the numerical results obtained using these two methods differ from each other. Assuming that the finite difference method gives accurate results, we estimate the error resulting from the use of physics-informed neural networks. We compare this estimate with surveys conducted among computer science students in order to assess the level of public trust among specialists in the numerical results obtained using artificial intelligence tools. In particular, we assess how reliable tsunami predictions obtained using physics-informed neural networks are and what the public perception
of the reliability of such predictions is.

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Author Biography

Alicja Niewiadomska, AGH University of Krakow

Alicja Niewiadomska was a master student at Faculty of Computer Science, AGH University of Krakow. She defended master thesis entitiled "Modeling of a tsunami caused by an earthquake on the coast of Chile using physics-informed neural networks (PINN)"

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