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  TEAM – The Transformer Earthquake Alerting Model

Münchmeyer, J., Bindi, D., Leser, U., Tilmann, F. (2021): TEAM – The Transformer Earthquake Alerting Model.
https://doi.org/10.5880/GFZ.2.4.2021.003

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Genre: Software
Other : V. 1.0

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 Creators:
Münchmeyer, J.1, Author           
Bindi, Dino2, Author           
Leser, Ulf3, Author
Tilmann, Frederik1, Author           
Affiliations:
12.4 Seismology, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum, ou_30023              
22.6 Seismic Hazard and Risk Dynamics, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum, ou_146032              
3External Organizations, ou_persistent22              

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Free keywords: seismology, earthquake, machine learning, real time assessment, python
 Abstract: TEAM, the Transformer Earthquake Alerting Model is a deep learning model for real time estimation of peak ground acceleration (TEAM), earthquake magnitude and earthquake location (TEAM-LM). This software package contains the joint implementation of both TEAM and the derivative TEAM-ML, as well as the scripts for training and evaluating these models. In addition, it contains scripts to download an early warning datasets for Japan and implementations of baseline approaches for the estimation of earthquake magnitude and peak ground acceleration. TEAM is implemented in Python.

TEAM and TEAM-ML have a variety of configuration parameters that are documented in the README. These configurations need to be provided in JSON format. In addition, multiple example configuration files are provided in the subdirectories pga_configs and magloc_configs. Please note that this implementation is intended for research purpose only. Production use is discouraged.

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Language(s): eng - English
 Dates: 20212021
 Publication Status: Finally published
 Pages: -
 Publishing info: Potsdam : GFZ Data Services
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.5880/GFZ.2.4.2021.003
 Degree: -

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