@misc{10481/93524,
year = {2024},
month = {6},
url = {https://hdl.handle.net/10481/93524},
organization = {Spanish Project
PID2022-143083NB-I00, “LEARNING”, funded by MICIU/AEI
/10.13039/501100011033},
organization = {FEDER, UE},
organization = {projects PROOF-FOREVER
(EUR2022.134044), ALARM (C.EXP. 022.UGR23) and
IMPROVE},
organization = {Project: PLEC2022-009271 “DigiVolCa”},
organization = {MCIN/AEI/10.13039/501100011033 and by EU
«NextGenerationEU/PRTR», 10.13039/501100011033},
publisher = {Frontiers},
title = {Universal machine learning approach to volcanic eruption forecasting using seismic features},
doi = {10.3389/feart.2024.1342468},
author = {Rey Devesa, Pablo and Carthy, Joe and Prudencio, Janire and Titos Luzón, Manuel Marcelino and Prudencio Soñora, Janire and Ibáñez, Jesús M. and Benítez, Carmen},
}