TY  - GEN
AU  - Gentili,Stefania
AU  - Giovambattista,Rita Di
AU  - Shcherbakov,Robert
AU  - Vallianatos,Filippos
AU  - Gentili,Stefania
AU  - Giovambattista,Rita Di
AU  - Shcherbakov,Robert
AU  - Vallianatos,Filippos
TI  - Statistics and Pattern Recognition Applied to the Spatio-Temporal Properties of Seismicity
SN  - books978-3-0365-4264-5
PY  - 2022///
CY  - Basel
PB  - MDPI - Multidisciplinary Digital Publishing Institute
KW  - Technology: general issues
KW  - bicssc
KW  - Environmental science, engineering & technology
KW  - system-analytical method
KW  - earthquake-prone areas
KW  - pattern recognition
KW  - clustering
KW  - machine learning
KW  - earthquake catalogs
KW  - high seismicity criteria
KW  - tidal triggering of earthquakes
KW  - seismic cycle
KW  - coulomb failure stress
KW  - preparatory phase
KW  - seismic prediction
KW  - earthquake forecasting
KW  - precursors
KW  - statistical seismology
KW  - earthquake likelihood models
KW  - seismicity patterns
KW  - New Zealand
KW  - California
KW  - smoothed seismicity methods
KW  - global seismicity
KW  - foreshocks and aftershocks
KW  - earthquake forecasting model
KW  - statistical methods
KW  - magnitude-frequency distribution
KW  - corner magnitude
KW  - tapered Pareto
KW  - tapered Gutenberg-Richter
KW  - epidemic type aftershock sequence model
KW  - extreme value distribution
KW  - Bayesian predictive distribution
KW  - seismicity clustering
KW  - DBSCAN algorithm
KW  - markovian arrival processes
KW  - numerical modeling
KW  - earthquake simulator
KW  - earthquake clustering
KW  - northern and central Apennines
KW  - n/a
N1  - Open Access
N2  - 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
UR  - https://mdpi.com/books/pdfview/book/5678
UR  - https://directory.doabooks.org/handle/20.500.12854/87480
ER  -