Evidence map›Paper›PMID 41654642›Full record

ArticleScientific reports2026

Single-station analysis of Campi Flegrei (Italy) seismic signals using multiscale entropy and unsupervised learning.

Alberico Grimaldi, Ortensia Amoroso, Silvia Scarpetta, Vincenzo Convertito, Ferdinando Napolitano, Giovanni Messuti, Paolo Capuano, Lucia Nardone, Guido Gaudiosi, Danilo Galluzzo

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Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Alberico GrimaldiDepartment of Physics E.R. Caianiello, University of Salerno, Fisicano, 84084, Salerno, Italy.
Ortensia AmorosoDepartment of Physics E.R. Caianiello, University of Salerno, Fisicano, 84084, Salerno, Italy. oamoroso@unisa.it.
Silvia ScarpettaDepartment of Physics E.R. Caianiello, University of Salerno, Fisicano, 84084, Salerno, Italy.
Vincenzo ConvertitoOsservatorio Vesuviano, Istituto Nazionale di Geofisica e Vulcanologia, Naples, Italy.
Ferdinando NapolitanoDepartment of Physics E.R. Caianiello, University of Salerno, Fisicano, 84084, Salerno, Italy.
Giovanni MessutiDepartment of Physics E.R. Caianiello, University of Salerno, Fisicano, 84084, Salerno, Italy.
Paolo CapuanoDepartment of Physics E.R. Caianiello, University of Salerno, Fisicano, 84084, Salerno, Italy.
Lucia NardoneOsservatorio Vesuviano, Istituto Nazionale di Geofisica e Vulcanologia, Naples, Italy.
Guido GaudiosiOsservatorio Vesuviano, Istituto Nazionale di Geofisica e Vulcanologia, Naples, Italy.
Danilo GalluzzoOsservatorio Vesuviano, Istituto Nazionale di Geofisica e Vulcanologia, Naples, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Seismic activity in volcanic regions such as Campi Flegrei (Italy) provides essential insights into subsurface dynamics and potential hazards. However, high background noise and continuous data volume challenge event detection and classification. Here, we apply a Self-Organizing Map (SOM) approach, combined with Linear Predictive Coding (LPC), STA/LTA ratios, and Multiscale Entropy (MSE), to analyze single-station seismic data. The method successfully identifies uncatalogued events and anomalies associated with fumarolic tremor, and reveals temporal relationships between clustering variation, [Formula: see text] emissions, and rainfall, suggesting environmental modulation. To assess the real-time applicability, the trained SOM was used on independent data from early 2025, confirming its ability to detect tremor intensification and anticipate a major local earthquake (Md 4.4). These results highlight the potential of entropy-based unsupervised learning for rapid seismic characterization and continuous volcano monitoring.

Indexed as

Campi Flegrei (Italy)Multiscale entropySeismic monitoring of a volcanoSingle-station analysisUnsupervised learning

Identifiers

PMID41654642
PMCPMC12946261

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