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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 …
Machine learning in volcanology: a review
A volcano is a complex system, and the characterization of its state at any given time is not
an easy task. Monitoring data can be used to estimate the probability of an unrest and/or an …
an easy task. Monitoring data can be used to estimate the probability of an unrest and/or an …
[HTML][HTML] A combination of feature selection and random forest techniques to solve a problem related to blast-induced ground vibration
In mining and civil engineering applications, a reliable and proper analysis of ground
vibration due to quarry blasting is an extremely important task. While advances in machine …
vibration due to quarry blasting is an extremely important task. While advances in machine …
Principal component analysis vs. self-organizing maps combined with hierarchical clustering for pattern recognition in volcano seismic spectra
K Unglert, V Radić, AM Jellinek - Journal of Volcanology and Geothermal …, 2016 - Elsevier
Variations in the spectral content of volcano seismicity related to changes in volcanic activity
are commonly identified manually in spectrograms. However, long time series of monitoring …
are commonly identified manually in spectrograms. However, long time series of monitoring …
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 …
Volcano-seismic transfer learning and uncertainty quantification with Bayesian neural networks
A Bueno, C Benitez, S De Angelis… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
Over the past few years, deep learning (DL) has emerged as an important tool in the fields of
volcano and earthquake seismology. However, these methods have been applied without …
volcano and earthquake seismology. However, these methods have been applied without …
Volcanic early warning using Shannon entropy: Multiple cases of study
The search for pre‐eruptive observables that can be used for short‐term volcanic forecast
remains a scientific challenge. Pre‐eruptive patterns in seismic data are usually identified by …
remains a scientific challenge. Pre‐eruptive patterns in seismic data are usually identified by …
Practical Volcano-Independent Recognition of Seismic Events: VULCAN.ears Project
Recognizing the mechanisms underlying seismic activity and tracking temporal and spatial
patterns of earthquakes represent primary inputs to monitor active volcanoes and forecast …
patterns of earthquakes represent primary inputs to monitor active volcanoes and forecast …
[HTML][HTML] Universal machine learning approach to volcanic eruption forecasting using seismic features
Introduction: Volcano seismology has successfully predicted several eruptions and includes
many reliable methods that have been adopted extensively by volcanic observatories; …
many reliable methods that have been adopted extensively by volcanic observatories; …
New insights on Mt. Etna's crust and relationship with the regional tectonic framework from joint active and passive P-wave seismic tomography
Abstract In the Central Mediterranean region, the production of chemically diverse volcanic
products (eg, those from Mt. Etna and the Aeolian Islands archipelago) testifies to the …
products (eg, those from Mt. Etna and the Aeolian Islands archipelago) testifies to the …