Machine learning for volcano-seismic signals: Challenges and perspectives

M Malfante, M Dalla Mura, JP Métaxian… - IEEE Signal …, 2018 - ieeexplore.ieee.org
Environmental monitoring is a topic of increasing interest, especially concerning the matter
of natural hazards prediction. Regarding volcanic unrest, effective methodologies along with …

Machine learning in volcanology: a review

R Carniel, S Guzman - Volcanoes-Updates in Volcanology, 2021 - air.uniud.it
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 …

[HTML][HTML] A combination of feature selection and random forest techniques to solve a problem related to blast-induced ground vibration

H Zhang, J Zhou, D Jahed Armaghani, MM Tahir… - Applied Sciences, 2020 - mdpi.com
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 …

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 …

ESeismic: Towards an Ecuadorian volcano seismic repository

N Pérez, D Benitez, F Grijalva, R Lara-Cueva… - Journal of Volcanology …, 2020 - Elsevier
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-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 …

Volcanic early warning using Shannon entropy: Multiple cases of study

P Rey‐Devesa, C Benítez, J Prudencio… - Journal of …, 2023 - Wiley Online Library
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 …

Practical Volcano-Independent Recognition of Seismic Events: VULCAN.ears Project

G Cortés, R Carniel, P Lesage, MÁ Mendoza… - Frontiers in Earth …, 2021 - frontiersin.org
Recognizing the mechanisms underlying seismic activity and tracking temporal and spatial
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

P Rey-Devesa, J Carthy, M Titos, J Prudencio… - Frontiers in Earth …, 2024 - frontiersin.org
Introduction: Volcano seismology has successfully predicted several eruptions and includes
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

A Díaz-Moreno, G Barberi, O Cocina, I Koulakov… - Surveys in …, 2018 - Springer
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 …