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Deep Green’s Function Tsunami Inversion
DOI:10.1109/LGRS.2025.3614237.png)
Abstract
En 中文
An important source of uncertainty in tsunami forecasting arises from uncertainty in the event’s initial conditions. In this work, we propose a dictionary-based inversion method that uses offshore sensor data to recover the initial ocean condition, allowing inversion of any tsunami event, and leading to reduced uncertainty in forecasts. We show that deep learning models can be used to address the computational requirements that arise from dictionary-based inversion. We validate our method using simulations of historic events.
Keywords:
Deep learning
Green’s function
tsunami
Journal
I
IF:
4.4
Papers:
570
Citations:
0

