Statistics and Pattern Recognition Applied to the Spatio-Temporal Properties of Seismicity

• Autore: Gentili Stefania
• Pubblicazione: Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
• Descrizione fisica: 1 online resource (180 p.)
• Soggetto topico: Environmental science, engineering and technology; Technology: general issues
• Soggetto non controllato: Bayesian predictive distribution; California; clustering; corner magnitude; coulomb failure stress; DBSCAN algorithm; earthquake catalogs; earthquake clustering; earthquake forecasting; earthquake forecasting model; earthquake likelihood models; earthquake simulator; earthquake-prone areas; epidemic type aftershock sequence model; extreme value distribution; foreshocks and aftershocks; global seismicity; high seismicity criteria; machine learning; magnitude-frequency distribution; markovian arrival processes; n/a; New Zealand; northern and central Apennines; numerical modeling; pattern recognition; precursors; preparatory phase; seismic cycle; seismic prediction; seismicity clustering; seismicity patterns; smoothed seismicity methods; statistical methods; statistical seismology; system-analytical method; tapered Gutenberg-Richter; tapered Pareto; tidal triggering of earthquakes
• Persona (resp. second.): GiovambattistaRita Di; ShcherbakovRobert; VallianatosFilippos; GentiliStefania
• Sommario/riassunto: Due to the significant increase in the availability of new data in recent years, as a result of the expansion of available seismic stations, laboratory experiments, and the availability of increasingly reliable synthetic catalogs, considerable progress has been made in understanding the spatiotemporal properties of earthquakes. The study of the preparatory phase of earthquakes and the analysis of past seismicity has led to the formulation of seismicity models for the forecasting of future earthquakes or to the development of seismic hazard maps. The results are tested and validated by increasingly accurate statistical methods. A relevant part of the development of many models is the correct identification of seismicity clusters and scaling laws of background seismicity. In this collection, we present eight innovative papers that address all the above topics. The occurrence of strong earthquakes (mainshocks) is analyzed from different perspectives in this Special Issue.
• Titolo autorizzato: Statistics and Pattern Recognition Applied to the Spatio-Temporal Properties of Seismicity
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910674369603321
• Lo trovi qui: Univ. Federico II