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Ensemble Learning for Earthquake Processing

Project description

ELEP


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ELEP

A ensemble-learning based toolkit for seismologists to make the best pick on earthquake phases by combining multiple predictions into the one.


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Prerequisites & installations

  • create a new environment using Anaconda
    >>> conda create --name myenv
    
  • install Seisbench
    >>> pip install seisbench
    
  • install other packages
    >>> pip install jupyter mpi4py
    
  • install our toolkit (under development)
    >>> pip install ELEP
    

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Features

workflow

This toolkit contains the following features:

  1. It provides broadband and multiband prediction workflows.
  2. It provides three ensemble estimation or combination approaches.
  3. It provides GPU-supported batch predictions on avilable datasets.
  4. It supports parallel predictions for real-time earthquake monitoring.
  5. It possess a good generalization capability.

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Demo

Please see the notebooks under the folder tutorials for more details.

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Citation

Yuan, C., Ni, Y., Lin, Y., Denolle, M., Ensemble Learning for Earthquake Detection and Phase Picking, 2023, in preparation.

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Contact

Congcong Yuan - cyuan@g.harvard.edu

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Project details


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Source Distribution

ELEP-0.0.2.tar.gz (10.3 kB view hashes)

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Built Distribution

ELEP-0.0.2-py3-none-any.whl (18.8 kB view hashes)

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