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Multi-Step Forecasting of Earthquake Magnitude Using Meta-Learning Based Neural Networks

Academic Article
Publication Date:
2022
abstract:
The prediction of the magnitude of an earthquake is still a challenge in the studies of seismic processes. The machine learning approaches have been developed recently to predict only the magnitude of next incoming earthquake using historical data. In this study, we combine neural networks with the meta-learning to predict not only the magnitude of the next earthquake, but also that of several earthquakes in the future. We successfully applied this novel method to predict the magnitude of Italian earthquakes above three different threshold magnitude. The experimental results show that the meta-learning based neural networks perform much better than the classical machine learning.
Iris type:
01.01 Articolo in rivista
Keywords:
Earthquakes; magnitude; meta-learning; neural networks; prediction
List of contributors:
Telesca, Luciano
Authors of the University:
TELESCA LUCIANO
Handle:
https://iris.cnr.it/handle/20.500.14243/416055
Published in:
CYBERNETICS AND SYSTEMS
Journal
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URL

https://biblioproxy.cnr.it:2171/doi/abs/10.1080/01969722.2021.1989170?journalCode=ucbs20
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