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Understanding the timing of eruption end using a machine learning approach to classification of seismic time series

Abstract:

The timing and processes that govern the end of volcanic eruptions are not yet fully understood, and there currently exists no systematic definition for the end of a volcanic eruption. Currently, end of eruption is established either by generic criteria (typically 90 days after the end of visual signals of eruption) or criteria specific to a given volcano. We explore the application of supervised machine learning classification methods: Support Vector Machine, Logistic Regression, Random Fore...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.jvolgeores.2020.106917

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Earth Sciences
Oxford college:
University College
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Earth Sciences
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Earth Sciences
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
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Publisher:
Elsevier Publisher's website
Journal:
Journal of Volcanology and Geothermal Research Journal website
Volume:
401
Article number:
106917
Publication date:
2020-05-25
Acceptance date:
2020-05-15
DOI:
ISSN:
0377-0273
Language:
English
Keywords:
Pubs id:
1105807
Local pid:
pubs:1105807
Deposit date:
2020-05-21

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