Neural networks and dynamical system techniques for volcanic tremor analysis

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R. Carniel

Abstract

A volcano can be seen as a dynamical system, the number of state variables being its dimension N. The state is usually confined on a manifold with a lower dimension f, manifold which is characteristic of a persistent «structural configuration». A change in this manifold may be a hint that something is happening to the dynamics of the volcano, possibly leading to a paroxysmal phase. In this work the original state space of the volcano dynamical system is substituted by a pseudo state space reconstructed by the method of time-delayed coordinates, with suitably chosen lag time and embedding dimension, from experimental time series of seismic activity, i.e. volcanic tremor recorded at Stromboli volcano. The monitoring is done by a neural network which first learns the dynamics of the persistent tremor and then tries to detect structural changes in its behaviour.

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1.
Carniel R. Neural networks and dynamical system techniques for volcanic tremor analysis. Ann. Geophys. [Internet]. 1996Nov.25 [cited 2022May21];39(2). Available from: https://www.annalsofgeophysics.eu/index.php/annals/article/view/3967
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