We present a novel method for coastal tsunami prediction utilizing a denoising autoencoder
(DAE) model, one of the deep learning algorithms. Our study focuses on the Tohoku coast …

The 1 January 2024, moment magnitude MW \left(M_W\right) 7.5 Noto Peninsula
earthquake ruptured in complex ways, challenging analysis of its tsunami generation. We …

Tsunami simulations require powerful computational resources to be performed efficiently.
Although the modern graphics processing units (GPUs) allow the acceleration of this kind of …

Given the recent developments in machine-learning technology, its application has rapidly
progressed in various fields of earthquake seismology, achieving great success. Here, we …

The shallow water equations (SWEs) can be used to model the spatio-temporal evolution of
free surface flows. The numerical resolution of realistic problems based on the 2D SWEs by …

Estimating coastal tsunami impact for early-warning or long-term hazard analysis requires
the calculation of inundation metrics such as flow-depth or momentum flux. Both applications …

In this study, we propose a scenario superposition method for real‐time tsunami wave
prediction. In the offline phase, prior to actual tsunami occurrence, hypothetical tsunami …

We investigate the use of the Senseiver, a transformer neural network designed for sparse
sensing applications, to estimate full-field surface height measurements of tsunami waves …

Probabilistic tsunami hazard and risk assessment (PTHA and PTRA) are vital methodologies
for computing tsunami risk and prompt measures to mitigate impacts. At large regional …

Earthquakes and tsunamis pose significant threats to Indonesia due to its unique geological
positioning at the convergence of four tectonic plates. This study focuses on classifying the …