Machine learning for volcano-seismic signals: Challenges and perspectives
Environmental monitoring is a topic of increasing interest, especially concerning the matter
of natural hazards prediction. Regarding volcanic unrest, effective methodologies along with …
of natural hazards prediction. Regarding volcanic unrest, effective methodologies along with …
[HTML][HTML] Automatic classification of seismic events within a regional seismograph network
J Kortström, M Uski, T Tiira - Computers & Geosciences, 2016 - Elsevier
This paper presents a fully automatic method for seismic event classification within a sparse
regional seismograph network. The method is based on a supervised pattern recognition …
regional seismograph network. The method is based on a supervised pattern recognition …
Characterization of volcanic regimes and identification of significant transitions using geophysical data: a review
R Carniel - Bulletin of Volcanology, 2014 - Springer
A volcano can be considered as a dynamical system, and each time series recorded at a
volcano can be interpreted as one of its observables. It is therefore theoretically possible to …
volcano can be interpreted as one of its observables. It is therefore theoretically possible to …
Automatic classification of volcano seismic signatures
The prediction of volcanic eruptions and the evaluation of associated risks remain a timely
and unresolved issue. This paper presents a method to automatically classify seismic events …
and unresolved issue. This paper presents a method to automatically classify seismic events …
A consistent high‐resolution catalog of induced seismicity in Basel based on matched filter detection and tailored post‐processing
Seismic monitoring of the Basel Enhanced Geothermal System has been running for more
than a decade. Yet the details of the long‐term behavior of its induced seismicity remained …
than a decade. Yet the details of the long‐term behavior of its induced seismicity remained …
ESeismic: Towards an Ecuadorian volcano seismic repository
In this work, we present the development, description, and performance evaluation of two
volcano seismological datasets: one containing raw seismic signals (MicSigV1) and another …
volcano seismological datasets: one containing raw seismic signals (MicSigV1) and another …
Support vector machine classification of seismic events in the Tianshan orogenic belt
L Tang, M Zhang, L Wen - Journal of Geophysical Research …, 2020 - Wiley Online Library
Discriminating between various types of seismic events is of significant scientific and
societal importance. We use a machine learning method employing support vector machine …
societal importance. We use a machine learning method employing support vector machine …
A deep active learning approach to the automatic classification of volcano-seismic events
Volcano-seismic event classification represents a fundamental component of volcanic
monitoring. Recent advances in techniques for the automatic classification of volcano …
monitoring. Recent advances in techniques for the automatic classification of volcano …
Exploring the unsupervised classification of seismic events of Cotopaxi volcano
This paper explores the use of six different clustering-based methods to classify long-period
and volcano-tectonic seismic events and to find possible overlap** signals of non …
and volcano-tectonic seismic events and to find possible overlap** signals of non …
Automatic multichannel volcano-seismic classification using machine learning and EMD
This article proposes the design of an automatic classifier using the empirical mode
decomposition (EMD) along with machine learning techniques for identifying the five most …
decomposition (EMD) along with machine learning techniques for identifying the five most …